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¿Vínculo entre los eventos hipoglucémicos en los diabéticos tipo 1 y la ansiedad clínica?

¿Vínculo entre los eventos hipoglucémicos en los diabéticos tipo 1 y la ansiedad clínica?


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Reconozco que la comunidad científica es consciente de que la vía del estrés químico está mediada por glucocorticoides. La respuesta de la vía se inicia como resultado de algún tipo de estrés (potencialmente químico, como glucosa baja) y el hipotálamo secreta la hormona liberadora de corticotropina que se une a los objetivos de la glándula pituitaria. Esto provoca la liberación de la hormona liberadora de adrenocorticotropina, que se une a objetivos en la corteza suprarrenal y promueve la producción de cortisol.

En caso de estrés hipoglucémico, las concentraciones de cortisol aumentan en todo el cuerpo como resultado de esta señalización de estrés. Para los diabéticos tipo 1 específicamente, la hipoglucemia es un efecto secundario común del tratamiento.

También reconozco que la respuesta de ansiedad está mediada en gran medida por la actividad de las amígdalas, y se sabe que las amígdalas tienen receptores para el cortisol (después de todo, son el centro del "miedo"). A partir de mi investigación, la morfología de las dendritas en esta estructura cerebral, así como otros centros para el estado de ánimo / emoción, se desplazan hacia patrones menos funcionales como consecuencia de la exposición crónica a glucocorticoides como el cortisol (Krugers 2010). Además, los glucocorticoides hacen que los receptores serotoninérgicos se vuelvan menos sensibles a la activación (van Riel 2003).

Entonces mis preguntas son:

Si el hipofuncionamiento de los receptores serotoninérgicos en el Núcleo de Raphe conduce a una activación excesiva de las neuronas del hipocampo y de la amígdala, que se cree que es uno de los principales mecanismos a través del cual se manifiesta la ansiedad, ¿por qué no tiene niveles crónicamente altos de cortisol, como resultado de la hipoglucemia? , ¿se ha implicado más en los trastornos de ansiedad en los diabéticos tipo 1? ¿Existe un vínculo con la depresión clínica desde aquí?

Los ISRS se usan constantemente para tratar la ansiedad a corto plazo, pero para los diabéticos, el meollo del problema parece ser la exposición crónica a niveles altos de cortisol. ¿Alguien ha estudiado o visto esto en sus prácticas / investigaciones?

Fuentes:

Krugers 2010 http://www.ncbi.nlm.nih.gov/pubmed/20820185

van Riel 2003 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3059694/


Abstracto

Objetivo

En muchas personas con diabetes, los síntomas desagradables y las consecuencias negativas asociadas con la hipoglucemia pueden provocar una ansiedad significativa o incluso un miedo a la hipoglucemia (FoH). Este miedo puede tener importantes implicaciones clínicas para el control de la diabetes. El objetivo de esta revisión es integrar la investigación existente sobre FoH (su medición, predictores, correlatos, impacto y tratamiento) y discutir sus implicaciones para el manejo de la diabetes y la educación del paciente.

Métodos

Se realizó una búsqueda bibliográfica utilizando Medline y Embase. La búsqueda se limitó a artículos de revistas publicados en inglés desde 1985 hasta 2007 inclusive. Se revisaron trescientos un resúmenes y 273 fueron rechazados por no ser pertinentes. Además de los 28 artículos incluidos, se identificaron seis artículos adicionales mediante búsquedas adicionales y se agregaron a esta revisión.

Resultados

FoH parece ser un fenómeno generalizado. Se mide principalmente mediante el uso de una escala específica, la Encuesta de miedo hipoglucémico (HFS). Hay una serie de factores que se relacionan con la probabilidad de que un individuo desarrolle FoH, incluido si existe un historial de hipoglucemia en un individuo, el tiempo transcurrido desde el primer tratamiento con insulina y un mayor nivel de variabilidad en el nivel de glucosa en sangre. FoH se ha relacionado tanto con el estado como con el rasgo de ansiedad, aunque la relación es compleja.

Conclusiones

Existe evidencia de que FoH puede tener un impacto negativo significativo en el manejo de la diabetes, el control metabólico y los resultados de salud posteriores. Existe evidencia de que el entrenamiento de concientización sobre la glucosa en sangre (BG) y la TCC pueden reducir los niveles de miedo y mejorar el manejo de la enfermedad. Se necesita más investigación sobre cómo surge FoH y las variables individuales que predicen su desarrollo. Además, se requiere una investigación bien diseñada para comprender mejor el impacto conductual y médico de FoH y las intervenciones para reducirlo.

Implicaciones de la práctica

Existe alguna evidencia que sugiere que las intervenciones que incluyen el entrenamiento de conciencia sobre la glucosa en sangre y la terapia cognitivo-conductual pueden reducir los niveles de miedo y mejorar el manejo de la enfermedad. Si bien muchos aspectos de FoH requieren más investigación bien diseñada, es evidente que este fenómeno puede tener un impacto importante en el manejo de la diabetes y debe abordarse específicamente en los programas de educación del paciente.


Descartar hipoglucemia

Si le preocupa que sus síntomas de ansiedad puedan ser causados ​​por una hipoglucemia, debe consultar con su médico lo antes posible para estar seguro. Para descartar oficialmente la hipoglucemia, se requiere un análisis de sangre. Sin embargo, el análisis de sangre NO debe realizarse inmediatamente después de un episodio de síntomas de ansiedad intensa. Esto se debe a que, después de uno de estos eventos, es posible que su nivel de azúcar en sangre ya esté peligrosamente bajo y necesite tiempo para recuperarse y evitar nuevos ataques.

Una prueba de hipoglucemia implica un ayuno de 12 horas, después de lo cual el médico puede tomar una muestra de su sangre y averiguar si ha alcanzado niveles peligrosamente bajos de glucosa (el azúcar en la sangre que le proporciona energía). Trate de calmarse durante este tiempo: esperar este tipo de prueba puede crear su propia ansiedad y, a menudo, el hambre y la sed también contribuyen a la ansiedad. Trate de mantenerse relajado y ocupado.

Un ataque de hipoglucemia no es divertido y es difícil funcionar durante él. Sin embargo, ya sea que tenga un ataque de ansiedad regular o un ataque de hipoglucemia, es perfectamente seguro comer algo que eleve sus niveles de azúcar en sangre en cualquier caso.

Si tiene que hacer esto con frecuencia (y descubre que le ayuda), probablemente tenga hipoglucemia, pero siempre es mejor consultar con un médico para estar seguro (ya que comer por estrés también puede ser un efecto de un trastorno de ansiedad y debería no se debe alentar, ya que puede convertirse en un mecanismo de afrontamiento insalubre).

Si tiene diabetes tipo 1 o tipo 2, un exceso de insulina (un medicamento que reduce el nivel de azúcar en la sangre) puede estar causando su hipoglucemia. Si este es el caso, hable con su médico sobre cómo ajustar su dosis de insulina.

De lo contrario, comer comidas saludables y regulares es crucial para mantener los niveles correctos de azúcar en sangre en su cuerpo. Seguir una nueva dieta de moda, excluir ciertos grupos de alimentos de su dieta o morirse de hambre para perder peso son formas comunes de que la ansiedad se cuele en su vida cuando no la necesita.

Al realizar un cambio en la dieta, asegúrese de obtener el asesoramiento de un profesional, como su médico de atención primaria o un nutricionista.


Epidemiología

La hipoglucemia es común con la diabetes tipo 1, particularmente en aquellos pacientes que reciben terapia intensiva con insulina. Según los informes, los episodios hipoglucémicos graves se han producido entre 62 y 320 episodios por cada 100 pacientes-año en la diabetes tipo 1. [3] & # x000a0 A diferencia de los pacientes que tienen diabetes tipo I y & # x000a0, los pacientes con diabetes tipo II sólo necesitan tratamiento con insulina, los pacientes con diabetes tipo II experimentan hipoglucemia. relativamente menos frecuente en comparación con los pacientes con diabetes tipo I. & # x000a0 Esto puede deberse, en parte, a farmacoterapias que no inducen hipoglucemia como la metformina. Se ha informado que la incidencia de hipoglucemia en pacientes con diabetes tipo II ha sido de aproximadamente 35 episodios durante 100 pacientes-año. [4] & # x000a0 No se han informado disparidades en los incidentes basados ​​en el género.


El desconocimiento de la hipoglucemia en la diabetes tipo 1 suprime las respuestas cerebrales a la hipoglucemia

3 Departamento de Psiquiatría, Facultad de Medicina de Yale, New Haven, Connecticut, EE. UU.

4 Centro de Ciencias Analíticas de Yale, Facultad de Salud Pública de Yale, New Haven, Connecticut, EE. UU.

5 Departamento de Cardiología, Nefrología y Endocrinología, Hospital Nordsjællands, Hillerød, Dinamarca.

Envíe la correspondencia a: Robert S. Sherwin, The Anlyan Center, TAC 147S, PO Box 208020, New Haven, Connecticut 06520, EE. UU. Teléfono: 203.785.4183 Correo electrónico: [email protected]

1 Sección de Endocrinología,

2 Departamento de Radiología e Imágenes Biomédicas y

3 Departamento de Psiquiatría, Facultad de Medicina de Yale, New Haven, Connecticut, EE. UU.

4 Centro de Ciencias Analíticas de Yale, Facultad de Salud Pública de Yale, New Haven, Connecticut, EE. UU.

5 Departamento de Cardiología, Nefrología y Endocrinología, Hospital Nordsjællands, Hillerød, Dinamarca.

Envíe la correspondencia a: Robert S. Sherwin, The Anlyan Center, TAC 147S, PO Box 208020, New Haven, Connecticut 06520, EE. UU. Teléfono: 203.785.4183 Correo electrónico: [email protected]

1 Sección de Endocrinología,

2 Departamento de Radiología e Imágenes Biomédicas y

3 Departamento de Psiquiatría, Facultad de Medicina de Yale, New Haven, Connecticut, EE. UU.

4 Centro de Ciencias Analíticas de Yale, Facultad de Salud Pública de Yale, New Haven, Connecticut, EE. UU.

5 Departamento de Cardiología, Nefrología y Endocrinología, Hospital Nordsjællands, Hillerød, Dinamarca.

Envíe la correspondencia a: Robert S. Sherwin, The Anlyan Center, TAC 147S, PO Box 208020, New Haven, Connecticut 06520, EE. UU. Teléfono: 203.785.4183 Correo electrónico: [email protected]

Encuentre artículos de Lacadie, C. en: JCI | PubMed | Google Académico

1 Sección de Endocrinología,

2 Departamento de Radiología e Imágenes Biomédicas y

3 Departamento de Psiquiatría, Facultad de Medicina de Yale, New Haven, Connecticut, EE. UU.

4 Centro de Ciencias Analíticas de Yale, Facultad de Salud Pública de Yale, New Haven, Connecticut, EE. UU.

5 Departamento de Cardiología, Nefrología y Endocrinología, Hospital Nordsjællands, Hillerød, Dinamarca.

Envíe la correspondencia a: Robert S. Sherwin, The Anlyan Center, TAC 147S, PO Box 208020, New Haven, Connecticut 06520, EE. UU. Teléfono: 203.785.4183 Correo electrónico: [email protected]

1 Sección de Endocrinología,

2 Departamento de Radiología e Imágenes Biomédicas y

3 Departamento de Psiquiatría, Facultad de Medicina de Yale, New Haven, Connecticut, EE. UU.

4 Centro de Ciencias Analíticas de Yale, Facultad de Salud Pública de Yale, New Haven, Connecticut, EE. UU.

5 Departamento de Cardiología, Nefrología y Endocrinología, Hospital Nordsjællands, Hillerød, Dinamarca.

Envíe la correspondencia a: Robert S. Sherwin, The Anlyan Center, TAC 147S, PO Box 208020, New Haven, Connecticut 06520, EE. UU. Teléfono: 203.785.4183 Correo electrónico: [email protected]

1 Sección de Endocrinología,

2 Departamento de Radiología e Imágenes Biomédicas y

3 Departamento de Psiquiatría, Facultad de Medicina de Yale, New Haven, Connecticut, EE. UU.

4 Centro de Ciencias Analíticas de Yale, Facultad de Salud Pública de Yale, New Haven, Connecticut, EE. UU.

5 Departamento de Cardiología, Nefrología y Endocrinología, Hospital Nordsjællands, Hillerød, Dinamarca.

Envíe la correspondencia a: Robert S. Sherwin, The Anlyan Center, TAC 147S, PO Box 208020, New Haven, Connecticut 06520, EE. UU. Teléfono: 203.785.4183 Correo electrónico: [email protected]

1 Sección de Endocrinología,

2 Departamento de Radiología e Imágenes Biomédicas y

3 Departamento de Psiquiatría, Facultad de Medicina de Yale, New Haven, Connecticut, EE. UU.

4 Centro de Ciencias Analíticas de Yale, Facultad de Salud Pública de Yale, New Haven, Connecticut, EE. UU.

5 Departamento de Cardiología, Nefrología y Endocrinología, Hospital Nordsjællands, Hillerød, Dinamarca.

Envíe la correspondencia a: Robert S. Sherwin, The Anlyan Center, TAC 147S, PO Box 208020, New Haven, Connecticut 06520, EE. UU. Teléfono: 203.785.4183 Correo electrónico: [email protected]

Encuentre artículos de Schmidt, C. en: JCI | PubMed | Google Académico

1 Sección de Endocrinología,

2 Departamento de Radiología e Imágenes Biomédicas y

3 Departamento de Psiquiatría, Facultad de Medicina de Yale, New Haven, Connecticut, EE. UU.

4 Centro de Ciencias Analíticas de Yale, Facultad de Salud Pública de Yale, New Haven, Connecticut, EE. UU.

5 Departamento de Cardiología, Nefrología y Endocrinología, Hospital Nordsjællands, Hillerød, Dinamarca.

Envíe la correspondencia a: Robert S. Sherwin, The Anlyan Center, TAC 147S, PO Box 208020, New Haven, Connecticut 06520, EE. UU. Teléfono: 203.785.4183 Correo electrónico: [email protected]

1 Sección de Endocrinología,

2 Departamento de Radiología e Imágenes Biomédicas y

3 Departamento de Psiquiatría, Facultad de Medicina de Yale, New Haven, Connecticut, EE. UU.

4 Centro de Ciencias Analíticas de Yale, Facultad de Salud Pública de Yale, New Haven, Connecticut, EE. UU.

5 Departamento de Cardiología, Nefrología y Endocrinología, Hospital Nordsjællands, Hillerød, Dinamarca.

Envíe la correspondencia a: Robert S. Sherwin, The Anlyan Center, TAC 147S, PO Box 208020, New Haven, Connecticut 06520, EE. UU. Teléfono: 203.785.4183 Correo electrónico: [email protected]

Encuentre artículos de Sejling, A. en: JCI | PubMed | Google Académico

1 Sección de Endocrinología,

2 Departamento de Radiología e Imágenes Biomédicas y

3 Departamento de Psiquiatría, Facultad de Medicina de Yale, New Haven, Connecticut, EE. UU.

4 Centro de Ciencias Analíticas de Yale, Facultad de Salud Pública de Yale, New Haven, Connecticut, EE. UU.

5 Departamento de Cardiología, Nefrología y Endocrinología, Hospital Nordsjællands, Hillerød, Dinamarca.

Envíe la correspondencia a: Robert S. Sherwin, The Anlyan Center, TAC 147S, PO Box 208020, New Haven, Connecticut 06520, EE. UU. Teléfono: 203.785.4183 Correo electrónico: [email protected]

Encuentre artículos de Belfort-DeAguiar, R. en: JCI | PubMed | Académico de Google | />

1 Sección de Endocrinología,

2 Departamento de Radiología e Imágenes Biomédicas y

3 Departamento de Psiquiatría, Facultad de Medicina de Yale, New Haven, Connecticut, EE. UU.

4 Centro de Ciencias Analíticas de Yale, Facultad de Salud Pública de Yale, New Haven, Connecticut, EE. UU.

5 Departamento de Cardiología, Nefrología y Endocrinología, Hospital Nordsjællands, Hillerød, Dinamarca.

Envíe la correspondencia a: Robert S. Sherwin, The Anlyan Center, TAC 147S, PO Box 208020, New Haven, Connecticut 06520, EE. UU. Teléfono: 203.785.4183 Correo electrónico: [email protected]

Encuentre artículos de Constable, R. en: JCI | PubMed | Google Académico

1 Sección de Endocrinología,

2 Departamento de Radiología e Imágenes Biomédicas y

3 Departamento de Psiquiatría, Facultad de Medicina de Yale, New Haven, Connecticut, EE. UU.

4 Centro de Ciencias Analíticas de Yale, Facultad de Salud Pública de Yale, New Haven, Connecticut, EE. UU.

5 Departamento de Cardiología, Nefrología y Endocrinología, Hospital Nordsjællands, Hillerød, Dinamarca.

Envíe la correspondencia a: Robert S. Sherwin, The Anlyan Center, TAC 147S, PO Box 208020, New Haven, Connecticut 06520, EE. UU. Teléfono: 203.785.4183 Correo electrónico: [email protected]

1 Sección de Endocrinología,

2 Departamento de Radiología e Imágenes Biomédicas y

3 Departamento de Psiquiatría, Facultad de Medicina de Yale, New Haven, Connecticut, EE. UU.

4 Centro de Ciencias Analíticas de Yale, Facultad de Salud Pública de Yale, New Haven, Connecticut, EE. UU.

5 Departamento de Cardiología, Nefrología y Endocrinología, Hospital Nordsjællands, Hillerød, Dinamarca.

Envíe la correspondencia a: Robert S. Sherwin, The Anlyan Center, TAC 147S, PO Box 208020, New Haven, Connecticut 06520, EE. UU. Teléfono: 203.785.4183 Correo electrónico: [email protected]

Encuentre artículos de Sherwin, R. en: JCI | PubMed | Google Académico

Publicado 30 de enero de 2018 - Más información

ANTECEDENTES. Entre los individuos no diabéticos, las disminuciones leves de glucosa alteran la actividad cerebral en regiones relacionadas con la recompensa, la motivación y el control ejecutivo. No está claro si estos efectos difieren en pacientes con diabetes mellitus tipo 1 (DM1) con y sin conciencia de la hipoglucemia.

MÉTODOS. Cuarenta y dos individuos (13 sujetos control sanos [HC], 16 individuos con DM1 con conciencia de hipoglucemia [T1DM-Aware] y 13 individuos con DM1T sin conciencia de hipoglucemia [T1DM-Sinware]) se sometieron a imágenes cerebrales de resonancia magnética funcional dependiente del nivel de oxígeno en sangre durante un Pinza hiperinsulinémica euglucémica (90 mg / dl)-hipoglucémica (60 mg / dl) de 2 pasos para la evaluación de las respuestas neurales a la hipoglucemia leve.

RESULTADOS. La hipoglucemia leve en sujetos con HC alteró la actividad en el caudado, la ínsula, la corteza prefrontal y la circunvolución angular, mientras que los sujetos conscientes de T1DM no mostraron cambios en la ínsula ni en el caudado, pero mostraron patrones de activación alterados en la corteza prefrontal y la circunvolución angular. Lo más sorprendente es que, en contraste directo con los sujetos HC y T1DM-Aware, los sujetos T1DM-Noware no mostraron ningún cambio inducido por hipoglucemia en la actividad cerebral. Estos hallazgos también se asociaron con respuestas contrarreguladoras hormonales atenuadas y puntuaciones de síntomas de hipoglucemia durante la hipoglucemia leve.

CONCLUSIÓN. En T1DM, y en particular en pacientes que no conocen T1DM, hay un embotamiento progresivo de las respuestas cerebrales en los neurocircuitos cortico-estriatales y fronto-parietales en respuesta a la hipoglucemia leve-moderada. Estos hallazgos tienen implicaciones para comprender por qué las personas con alteración del conocimiento de la hipoglucemia no responden adecuadamente a la caída de los niveles de glucosa en sangre.

FONDOS. Este estudio fue apoyado en parte por las subvenciones del NIH R01DK020495, P30 DK045735, K23DK109284, K08AA023545. El Centro de Yale para la Investigación Clínica cuenta con el apoyo de un premio NIH Clinical Translational Science Award (UL1 RR024139).

Los pacientes con diabetes mellitus tipo 1 (T1DM) han estado limitados durante mucho tiempo por los efectos adversos de la hipoglucemia inducida por insulina. El Diabetes Control and Complications Trial (DCCT) estableció los beneficios de restaurar la glucosa media en sangre a niveles casi normales en pacientes con DM1, y si bien esto ha producido beneficios claros en términos de las complicaciones microvasculares y macrovasculares de la DM1, para muchas personas, la El uso generalizado de la terapia intensificada con insulina ha dado lugar a una tasa mucho más alta de hipoglucemia grave (1). Los episodios frecuentes de hipoglucemia pueden hacer que la hipoglucemia no se dé cuenta, lo que impide que los pacientes tomen medidas correctivas al comer. Por lo tanto, para muchos pacientes con DM1, el miedo inmediato a la hipoglucemia supera el miedo a las complicaciones a largo plazo (2, 3).

En sujetos no diabéticos, la hipoglucemia es rara porque, en respuesta a la disminución de los niveles de glucosa en sangre, se desencadena una respuesta fisiológica integrada que suprime la secreción de insulina endógena, aumenta la liberación de hormonas contrarreguladoras y provoca la conciencia de la hipoglucemia, que actúan juntas para restaurar rápidamente la euglucemia al estimular producción de glucosa y consumo de alimentos. Anteriormente hemos informado sobre el uso de la técnica de pinzamiento de glucosa junto con imágenes de resonancia magnética funcional (fMRI), señales visuales de alimentos y medidas de comportamiento que las regiones del cerebro involucradas en estimular la motivación para comer son exquisitamente sensibles a pequeñas reducciones de glucosa. En humanos sanos, reducciones leves de la glucosa plasmática (

68 mg / dl) que no fueron suficientes para aumentar las hormonas contrarreguladoras fueron suficientes para activar el flujo sanguíneo hipotalámico (4), así como para modular la motivación / recompensa del cerebro y las respuestas de control ejecutivo a las señales alimentarias, lo que a su vez resultó en un mayor deseo por la alta. alimentos calóricos (5).

En la DM1, este sistema crítico de defensa contra la hipoglucemia puede interrumpirse en todos los niveles. La pérdida de insulina endógena y la dependencia de la administración periférica de hormonas exógenas hacen imposible una rápida reducción de la insulina. La destrucción de las células β también está relacionada con la pérdida de respuestas del glucagón a la hipoglucemia, un defecto que se desarrolla en casi todos los pacientes con DM1 (6, 7). Como resultado, los pacientes con DM1 son particularmente vulnerables a alteraciones en la liberación de epinefrina, que comúnmente sigue a una hipoglucemia iatrogénica inducida por insulina (8 - 10).

Los episodios frecuentes de hipoglucemia en individuos con DM1 comúnmente conducen a insuficiencia autónoma asociada a hipoglucemia (HAAF), por lo que se requieren niveles de glucosa en sangre significativamente más bajos para provocar una respuesta hormonal contrarreguladora, así como conciencia sintomática de hipoglucemia (2, 3, 9). Se desconoce si la pérdida de conciencia de la hipoglucemia también se acompaña de una falla en la activación del impulso de comer, que es clínicamente la forma más eficaz de revertir la hipoglucemia. Un estudio que utilizó fMRI informó que la conectividad funcional en las regiones del cerebro que han sido implicadas en el control de la conducta alimentaria, incluidos los ganglios basales, la ínsula y la corteza prefrontal, están alteradas en individuos con DMT1 (11). Sin embargo, este estudio no examinó los efectos específicos del HAAF y el desconocimiento de la hipoglucemia sobre la actividad cerebral. Otro estudio en un pequeño número de personas con DM1 que eran conscientes o no de la hipoglucemia mediante la exploración por PET con [18 F] fluoro-2-desoxiglucosa (FDG) sugirió que la hipoglucemia aguda puede aumentar la captación de FDG en el estriado ventral y que una pequeña disminución de esta la respuesta puede haber ocurrido en pacientes inconscientes (12). Sin embargo, es posible que la captación de FDG no refleje con precisión la captación de glucosa durante la hipoglucemia, ya que la hipoglucemia aguda (y probablemente la hipoglucemia antecedente) altera la constante acumulada utilizada para calcular la captación de glucosa (13).

Cabe señalar que los estudios anteriores que utilizaron fMRI o PET para evaluar el impacto de la hipoglucemia en el cerebro entre las personas con DM1 han utilizado objetivos glucémicos muy bajos (típicamente 50 mg / dl o menos). Sin embargo, desde una perspectiva clínica, cuando la glucemia de un paciente con DM1 cae en el rango bajo de 50 mg / dl, es posible que ya tenga un riesgo significativamente mayor de morbilidad y mortalidad asociadas a la hipoglucemia debido a que no se activan adecuadamente las múltiples capas de protección. contra la hipoglucemia. Por lo tanto, en este estudio, buscamos específicamente determinar cómo las personas con DM1 con o sin hipoglucemia inconsciente responden a grados más leves de hipoglucemia en un esfuerzo por distinguir de manera más efectiva los defectos del SNC en un momento anterior que conduce a la inconsciencia en el curso del desarrollo moderado de hipoglucemia. hipoglucemia severa. Para hacer esto, utilizamos un escaneo cerebral por resonancia magnética funcional junto con una técnica de pinzamiento hipoglucémico euglucémico hiperinsulinémico de 2 pasos para investigar cómo la actividad cerebral regional, en particular los neurocircuitos que impulsan la conducta alimentaria, se alteran entre los individuos con DM1 con inconsciencia de hipoglucemia (T1DM-Inconsciente) como en comparación con los pacientes con conciencia conservada (T1DM-Aware), así como con sujetos sanos de control no diabético (HC) durante la hipoglucemia aguda leve-moderada (objetivo

En este estudio participaron trece personas con HC, 16 personas con T1DM-Aware según la evaluación de Clarke (14) y 13 personas con T1DM-Sinware. Las características demográficas y clínicas se presentan en la Tabla 1. En comparación con los individuos con HC, tanto los individuos conscientes de T1DM como los individuos sin T1DM eran similares en edad, sexo y educación. Los individuos sin T1DM eran un poco mayores (PAG = 0.01), tuvo una mayor duración de la enfermedad (PAG & lt 0,001), y tenía un IMC ligeramente más alto (PAG = 0,003) que el grupo T1DM-Aware. Las personas sin T1DM también tuvieron tasas significativamente más altas de episodios hipoglucémicos graves en el año anterior (PAG = 0,03). Los grupos T1DM-Aware y T1DM-Unware fueron indistinguibles en términos de porcentaje de hemoglobina glucosilada (HbA1c), y no hubo diferencias entre los 3 grupos para el género y la educación, así como las medidas de trastornos alimentarios y función cognitiva (Tabla 1).

Pinza euglucémico-hipoglucémica hiperinsulinémica de dos pasos

Como se ve en la Figura 1B, ambos grupos de individuos con T1DM tenían niveles de glucosa en sangre moderadamente más altos al comienzo del estudio en comparación con los sujetos con HC. Sin em % IC –4,1, 14,7], PAG = 0,27). Además, a partir de los 25 minutos, no hubo diferencias estadísticamente significativas en las comparaciones por pares de los niveles de glucosa en plasma entre T1DM-Sinware en comparación con T1DM-Aware (PAG = 0,11), así como los participantes de HC (PAG = 0,14). En particular, durante los tiempos de adquisición de datos dependientes del nivel de oxígeno en sangre (BOLD) de la resonancia magnética funcional (euglucemia a los 45-60 minutos e hipoglucemia a los 90-105 minutos), los niveles de glucosa plasmática fueron prácticamente idénticos en los 3 grupos y estaban en el objetivo (promedio plasmático glucosa a euglucemia 93,0 ± 1,9 mg / dl e hipoglucemia 58,9 ± 1,1 mg / dl) (Figura 1B). Tampoco hubo diferencias en los niveles de insulina plasmática entre los grupos (PAG = 0,76) a lo largo del tiempo. Además, no hubo diferencias significativas entre los grupos en las tasas medias de infusión de glucosa (GIR) durante la euglucemia (GIR [mg / kg / min], HC 9,5 ± 1,1 frente a T1DM-Aware 8,2 ± 1,4 frente a T1DM-Sinware 7,0 ± 0,9 , PAG = 0,35), así como durante la hipoglucemia (HC 7,2 ± 0,8 frente a T1DM-Aware 6,6 ± 0,7 frente a T1DM-Sinware 4,9 ± 0,8, PAG = 0.12).

Diseño del estudio. (A) Representación esquemática de la pinza de hipoglucemia euglucémica hiperinsulinémica de 2 pasos durante la exploración fMRI BOLD en respuesta a señales visuales. (B) Niveles de glucosa plasmática de control saludable (norte = 13), compatible con T1DM (norte = 16) y T1DM-Desconocido (norte = 13) durante el estudio. Los datos se presentan como la media ± SEM. Las comparaciones estadísticas se realizaron mediante el ajuste de regresión lineal de modelo mixto por edad, sexo e IMC.

Respuestas hormonales y sintomáticas a la hipoglucemia

Los niveles medios de epinefrina, norepinefrina, glucagón y cortisol plasmáticos en euglucemia e hipoglucemia se muestran en la Figura 2. Los niveles de epinefrina basales fueron diferentes entre los grupos (ANOVA PAG = 0,04). Esta diferencia se debió principalmente a la diferencia entre T1DM-Sinware en comparación con los participantes con HC (PAG = 0,024). Los pacientes T1DM-Sinware y T1DM-Aware no fueron significativamente diferentes (PAG = 0,07). En particular, los niveles de epinefrina plasmática aumentaron significativamente en respuesta a la hipoglucemia en los 3 grupos. Los sujetos con HC y T1DM-Aware tuvieron un aumento de casi 3 veces en los niveles de epinefrina, mientras que los individuos con T1DM-Sinware tuvieron una respuesta mucho más modesta, es decir, solo un aumento del 60% al 70% por encima de los niveles euglucémicos. Por el contrario, solo los HC tuvieron un aumento significativo de glucagón y cortisol plasmáticos durante la fase hipoglucémica del estudio. No se detectaron cambios significativos en la noradrenalina plasmática en los 3 grupos durante este estímulo hipoglucémico relativamente leve.

Respuestas hormonales a la hipoglucemia leve en un control saludable (norte = 13), compatible con T1DM (norte = 16) y T1DM-Desconocido (norte = 13) durante el estudio. (A) Epinefrina, (B) norepinefrina, (C) glucagón, (D) cortisol. Las barras abiertas denotan euglucemia, las barras negras denotan hipoglucemia. Los valores de euglucemia se promediaron a partir de los obtenidos a los 45-60 minutos de la pinza. Los valores de hipoglucemia se promediaron a partir de los obtenidos a los 90-105 minutos de pinzamiento. Los datos se presentan como la media ± SEM. *PAG & lt 0.05 por muestras pareadas t prueba.

Mientras estaban en el escáner y antes de las adquisiciones de fMRI BOLD (a los 30 y 75 minutos), se les pidió a los participantes que calificaran sus síntomas de hipoglucemia utilizando la puntuación de hipoglucemia de Edimburgo (15). Tanto los sujetos T1DM-Aware como los HC mostraron un aumento estadísticamente significativo en la respuesta de los síntomas durante la hipoglucemia, mientras que no hubo cambios significativos en los síntomas en el grupo T1DM-Unware (Figura 3). Curiosamente, los síntomas de hipoglucemia fueron diferentes entre los grupos durante la hipoglucemia (HC, 23,9 ± 7,0 T1DM-Aware, 35,9 ± 14,2 T1DM-Sinware, 28,4 ± 12,4 ANOVA PAG (PAG = 0,009). Además, durante la hipoglucemia, los síntomas de la hipoglucemia se correlacionaron significativa y positivamente con los niveles de epinefrina plasmática para los individuos conscientes de T1DM (ρ = 0,58, PAG = 0.02), pero no para T1DM-Desconocido (PAG = 0,54). Cabe destacar que un participante que no conocía la DM1 según la puntuación de Clarke tuvo un aumento muy pronunciado en los niveles de epinefrina plasmática durante la hipoglucemia leve (euglucemia 47 pg / ml, hipoglucemia máxima 329 pg / ml) sin embargo, este participante tuvo cambios mínimos en la hipoglucemia puntuaciones de síntomas durante la hipoglucemia aguda (puntuación de Edimburgo euglucemia 33, hipoglucemia 39), a pesar de alcanzar los niveles de glucosa objetivo durante las porciones de euglucemia e hipoglucemia de la pinza. Como resultado, todos los análisis basados ​​en fMRI se realizaron con y sin este participante. Dado que no hubo cambios significativos en los resultados, este participante fue incluido en todos los análisis posteriores.

Puntuaciones de síntomas de hipoglucemia en control sano (norte = 13), compatible con T1DM (norte = 16) y T1DM-Desconocido (norte = 13). Los síntomas de hipoglucemia de la puntuación de síntomas de hipoglucemia de Edimburgo se administraron en una escala Likert (1 - 7) y se sumaron los resultados. Las barras abiertas denotan euglucemia, las barras negras denotan hipoglucemia. Los datos se presentan como la media ± SEM. *PAG & lt 0.05 por muestras pareadas t prueba.

Respuestas neuronales a la hipoglucemia leve

Relación global entre grupos y glucemia (efectos grupo × condición). En los 3 grupos, hubo una diferencia de grupo significativa en la respuesta cerebral a la hipoglucemia y euglucemia en el cuerpo estriado derecho (dorsal / ventral), particularmente en el caudado (Figura 4) incluso después de ajustar por edad e IMC y usar el umbral estándar actual para significado de PAG menos de 0,001 (todo el cerebro, error familiar [FWE] corregido) (16). Para dar una sensación de direccionalidad del cambio, se definió una región de interés a partir del grupo significativo en el caudado derecho y se extrajeron los pesos β del modelo lineal general medio (GLM) para cada sujeto. En respuesta a la hipoglucemia, los sujetos con HC tuvieron una actividad relativamente disminuida en el caudado, mientras que los individuos T1DM-Aware y T1DM-Unware tuvieron cambios mínimos (Figura 4B). En los 3 grupos, no encontramos ninguna significativa (en PAG & lt 0,001) interacciones entre grupo × glucemia × tarea o grupo × tarea. Por lo tanto, todos los análisis que utilizaron los 3 grupos se colapsaron en las tareas (señales visuales alimentarias y no alimentarias). Además, aunque los 3 grupos tenían niveles de glucosa plasmática similares 20 minutos antes del momento de las adquisiciones de BOLD, el grupo T1DM-Aware tenía niveles de glucosa plasmática más altos al inicio de las pinzas. Evaluar si estas diferencias en los niveles iniciales de glucosa afectaron la actividad cerebral durante las adquisiciones de euglucemia BOLD (

45 minutos después), evaluamos las interacciones entre grupos y entre grupos en la euglucemia sola y no encontramos diferencias significativas.

Grupo × efectos de la glucemia. (A) Cortes axiales que muestran las diferencias en las respuestas cerebrales a la hipoglucemia leve en comparación con la euglucemia en los 3 grupos (covariado para la edad y el IMC, umbral de PAG & lt 0,001, 2 colas, FWE con corrección de todo el cerebro). (B) Región de interés (ROI) identificada a partir de un grupo significativo en el cuerpo estriado derecho (caudado). Pesos β del modelo lineal general extraídos de cada participante, presentados como media (IC del 95%). Control saludable norte = 13, compatible con T1DM norte = 16, T1DM-Desconocido norte = 13.

Luego, examinamos la respuesta de la actividad cerebral de cada grupo a la hipoglucemia por separado (la Figura 5 y el material complementario de la Tabla 1 complementaria están disponibles en línea con este artículo https://doi.org/10.1172/JCI97696DS1). Los sujetos con HC, T1DM-Aware y T1DM-Unware tenían patrones sorprendentemente diferentes de respuestas cerebrales a la hipoglucemia leve, incluso después de ajustar por edad e IMC. En particular, en respuesta a la hipoglucemia, los sujetos con HC tenían una actividad relativamente disminuida en el cuerpo estriado / caudado ventral, la ínsula, la corteza orbitofrontal (OFC), la corteza prefrontal ventromedial (vmPFC), la corteza prefrontal ventrolateral (vlPFC), la corteza prefrontal dorsolateral (dlPFC), y circunvolución angular izquierda. In contrast, while the T1DM-Aware individuals also had relatively decreased activity in the vmPFC and OFC, they did not have any significant differences in activity in the caudate, insula, or dlPFC. Interestingly, the T1DM-Aware individuals had relatively increased activity in the inferior parietal lobe, particularly the right angular gyrus as well as the right vlPFC. In contrast, T1DM-Unaware individuals showed no significant changes in brain activity in any of the regions that were different among the other 2 groups.

Differences in regional brain responses between mild hypoglycemia and euglycemia conditions. Axial slices of healthy control (norte = 13), T1DM-Aware (norte = 16), and T1DM-Unaware (norte = 13) subjects showing differences in brain responses to mild hypoglycemia (Hypo-Eu) (covaried by age and BMI, threshold of PAG < 0.001, 2-tailed, FWE whole-brain corrected). Regions identified as: A = ventromedial prefrontal cortex (vmPFC) B = orbitofrontal cortex (OFC) C = right ventral striatum/caudate D = right insula E = ventrolateral prefrontal cortex (vlPFC) F = dorsolateral prefrontal cortex (dlPFC) G = angular gyrus.

Given that changes in plasma epinephrine levels are believed to be a particularly sensitive marker for defective counterregulation among T1DM individuals, we assessed the relationship between changes in plasma epinephrine levels and changes in brain responses in the regions identified in Figure 5. A smaller change in plasma epinephrine levels was associated with a smaller degree of deactivation in the striatum/caudate (ρ = –0.43, PAG = 0.005), vmPFC (ρ = –0.46, PAG = 0.003), right insula (ρ = –0.37, PAG = 0.02), vlPFC (ρ = –0.34, PAG = 0.03), and angular gyrus (ρ = –0.41, PAG = 0.007), consistent with the association of the blunted epinephrine response with the blunted brain responses. There were no associations between brain activity in any of the above regions and epinephrine levels at euglycemia or hypoglycemia alone. Among the T1DM subjects, the Edinburgh hypoglycemia symptom score correlated inversely with activity only in the vmPFC during hypoglycemia (ρ = –0.410, PAG = 0.03).

Effect of hypoglycemia unawareness on brain responses to high-calorie food cues

To address the question of whether hypoglycemia unawareness modulates the brain’s response to hypoglycemia while viewing high-calorie food stimuli, we performed an analysis focused on only the T1DM-Aware and T1DM-Unaware groups. While viewing high-calorie food cues (

75% of the high-calorie cues were also high carbohydrate), there was a significant group × glycemia interaction (PAG < 0.001), even after covarying for age, BMI, and duration of diabetes. This interaction was not present under non-food visual stimuli conditions. Notably, T1DM-Aware individuals had a significant decrease in brain activity during high-calorie food in the medial OFC (Brodmann area 11), while T1DM-Unaware individuals showed no statistically significant change in brain activity in this region (Figure 6). There were no significant correlations between brain activity in this region and counterregulatory hormones.

Brain responses to high-calorie food cues. Axial brain slices (Z = –17) of change in brain response to mild hypoglycemia (Hypo – Eu) while viewing high-calorie food cues and non-food cues in (A) T1DM-Aware (norte = 16) and (B) T1DM-Unaware (norte = 13) participants (covaried by age, duration of diabetes, and BMI, threshold of PAG < 0.001, 2-tailed, FWE whole-brain corrected). Data presented as the mean (95% CI).

In this study, we show that hypoglycemia unawareness in T1DM patients is associated with a diminished brain response to mild hypoglycemia (plasma glucose

60 mg/dl). Moreover, the pattern of loss of brain responses appears to involve cortico-striatal and fronto-parietal neurocircuits that are known to play important roles in regulating motivation and goal-directed behavior as well as attention, and thus are likely to have implications for understanding why individuals with hypoglycemia unawareness fail to respond appropriately to falling blood glucose levels.

The basal ganglia, and in particular the caudate, has been consistently shown in studies across species and imaging modalities to play an important role in the ability to respond appropriately to environmental changes and to regulate goal-directed behavioral inputs ( 17 – 21 ). The caudate has direct physical and functional connections with executive control regions in the frontal cortex including the medial, ventral, and dorsolateral PFC ( 22 , 23 ). Among HC individuals, mild hypoglycemia was sufficient to elicit changes in the caudate, cortical regions such as the vmPFC and vlPFC, and the insula, which is consistent with previous studies that have shown that the caudate, PFC, and insula are responsive to changes in circulating glucose levels ( 5 , 12 , 24 , 25 ). In contrast, T1DM-Aware individuals had altered patterns of cortico-striatal activity with no significant changes in the caudate or insula during hypoglycemia. We also observed differences across groups in the patterns of activation/deactivation in the dlPFC and angular gyrus. The angular gyrus, located in the inferior parietal lobe, has direct projections to the dlPFC ( 26 ) and together they are part of a larger, well-studied, fronto-parietal circuit ( 27 – 29 ). The angular gyrus, in particular, has been shown to play a role in regulating how one’s attention shifts towards higher salient stimuli ( 30 – 33 ). Interestingly, among HC subjects, mild hypoglycemia induced changes in activity in the left dlPFC and left angular gyrus, which is consistent with a previous study in HC subjects during hypoglycemia (plasma glucose 50 mg/dl) while performing cognitive tasks ( 34 ). In contrast, T1DM-Aware individuals had no brain responses in the left dlPFC or left angular gyrus, but instead showed markedly increased activity in the right angular gyrus. Taken together with our findings that T1DM-Aware individuals had higher ratings for symptoms at hypoglycemia, these observations suggest that increased activity in inferior parietal lobe/angular gyrus may be a compensatory adaptation to the disruption in cortico-striatal and fronto-parietal neurocircuits that are involved in sensing mild hypoglycemia. The markedly increased angular gyrus activity seen in the T1DM-Aware group during mild hypoglycemia may reflect differences in attention to or sensing of the stimulus ( 35 ). Thus, the T1DM-Aware individuals may have heightened awareness to hypoglycemia sensory inputs compared with HC subjects, which would be consistent with their higher reported ratings of hypoglycemia symptoms both at euglycemia and at hypoglycemia.

Most strikingly, compared with T1DM-Aware and HC subjects, the T1DM-Unaware participants showed virtually no changes in brain activity in response to mild hypoglycemia. Very little is known about the impact of hypoglycemia unawareness on regional brain responses however, these findings would be consistent with the blunted symptom scores as well as the blunted counterregulatory hormone responses to hypoglycemia observed in the T1DM-Unaware group. The underlying mechanism mediating the lack of change among the T1DM-Unaware individuals remains uncertain however, it is likely due to brain adaptations to frequent episodes of severe hypoglycemia in the preceding year of the study. Recurrent hypoglycemia alters brain glucose transport kinetics as well as promotes increased utilization of alternate fuels such as monocarboxylic acids (lactate, ketones, and acetate) in humans when the availability of glucose diminishes ( 36 , 37 ). Furthermore, T1DM individuals with hypoglycemia unawareness may have alterations in cerebral blood flow during hypoglycemia ( 38 , 39 ), which may also affect BOLD signal. Interestingly, a recent study has reported that individuals with T1DM and hypoglycemia unawareness have increased cerebral blood flow during acute hypoglycemia compared with T1DM-Aware and HC subjects ( 39 ). The current findings would be consistent with these observations that the brain adapts to ensure sufficient substrate (glucose) delivery to the brain. In keeping with these human studies, data in rodents have also demonstrated that prior exposure to hypoglycemia induces upregulation of blood-brain-barrier glucose transport, leading to more efficient glucose utilization during hypoglycemia ( 40 , 41 ). Thus, the lack of change in brain activity among T1DM-Unaware individuals in response to mild hypoglycemia may be the culmination of a variety of adaptive changes in cerebral blood flow, glucose transport, cerebral glucose metabolism, or some combination of each of these factors.

It is important to note that induction of hypoglycemia results in a series of dynamic changes in brain activation and deactivation, and thus time intervals when the scans are acquired over the course of hypoglycemia may directly impact the directionality and regional changes observed ( 24 ). This, as well as other factors such as hypoglycemia target, timing of image acquisition, and imaging modality, may all contribute to the heterogeneity of brain responses to hypoglycemia previously reported in the literature. For example, we did not observe hypoglycemia-induced changes in the hypothalamus, which has been reported by some groups ( 25 ), but not others ( 42 ) to be altered during hypoglycemia in T1DM individuals. Thus, our findings must be interpreted cautiously given that we are only observing a snapshot of the dynamic brain changes produced over the course of falling blood glucose levels, a critical time for prevention of hypoglycemia-induced brain injury.

Importantly, it remains uncertain whether lower glycemic thresholds will be able to elicit changes in brain activation responses among T1DM-Unaware individuals and whether the brain responses will be in a similar pattern to that observed among T1DM-Aware individuals. Studies of glucose transport kinetics in hypoglycemia T1DM-Unaware individuals have found that glucose transport is preserved even at glucose levels as low as 50 mg/dl ( 43 ). However, it remains uncertain whether lower glucose thresholds are the only difference between T1DM-Aware and -Unaware individuals. Thus, this current study highlights the need for further studies designed to assess the contribution of additional factors such as age of onset of diabetes, duration of diabetes, and severity of diabetes during childhood/adolescence when the brain is still developing in determining the propensity for developing hypoglycemia unawareness. Furthermore, whether these changes are reversible and whether strict avoidance of hypoglycemia can restore brain responses remains to be assessed. Of note, prior studies using strict avoidance of hypoglycemia have also resulted in worsening of glycemic control ( 44 – 46 ), which could also have an impact on glucose transport capacity into the brain.

Because one of the earliest and best defenses against falling blood glucose levels is to eat, we also examined the brain responses to high-calorie/high-carbohydrate food cues. Among nondiabetic individuals, high-calorie food cues have been shown to elicit robust changes in brain activity in reward, motivation, and executive control regions during both euglycemia ( 47 ) and mild hypoglycemia ( 5 ). Consistent with these findings reported in nondiabetic individuals, the current data demonstrate that T1DM-Aware individuals also had a pronounced change in the medial OFC when viewing high-calorie food cues that was not present when looking at pictures of non-food objects. Notably, the medial OFC plays an important role in reward-guided decision making ( 48 , 49 ). Furthermore, because it has dense direct connections with the hypothalamus ( 50 , 51 ), it has been shown to play a particularly important role in regulating feeding behavior ( 52 – 54 ). Thus, it is particularly noteworthy that in contrast to T1DM-Aware individuals, high-calorie food cues had no effect on medial OFC brain activity during mild hypoglycemia in T1DM-Unaware individuals, suggesting a diminished drive to eat, which may be a critical early defect in the defense against hypoglycemia. Interestingly, we found no relationship between changes in brain activity to high-calorie foods and the counterregulatory hormone response. Whether the lack of brain response is due to intrinsic CNS differences or secondary to the blunted rise in circulating counterregulatory hormone levels remains unclear and further studies will be needed to address this question and prove causality. However, given that in nondiabetic subjects changes in brain activity induce and occur prior to changes in counterregulatory hormones ( 4 ), it is likely that changes in brain activity are not primarily driven by the counterregulatory response, but rather play the key role in protecting the brain by initiating appropriate defenses against falling glucose levels. Prior studies have also noted a dissociation between counterregulatory hormone responses and awareness of hypoglycemia ( 45 ).

It is noteworthy that there are some considerations and limitations to the current study. While we defined our groups using widely accepted and validated questionnaires for hypoglycemia unawareness, the Clarke and Gold scores, these are subjective reports and we did not collect data on glycemic variability and objective rates of hypoglycemia in the months preceding our studies. In addition, our T1DM-Unaware participants were approximately 10 years older and had diabetes for a longer duration than the T1DM-Aware group. Although we covaried for age, BMI, and duration of diabetes, our findings among the T1DM-Unaware individuals should still be interpreted cautiously with recognition that it may be very difficult experimentally to separate the effects of age and longer duration of T1DM from the effects of hypoglycemia unawareness itself. Of note in this regard, increasing age has been associated with increases in baseline epinephrine levels ( 55 ) and our T1DM-Unaware cohort was slightly older and had higher baseline epinephrine levels however, we did not observe any relationships between epinephrine levels at euglycemia or hypoglycemia and brain responses. Furthermore, prior studies have examined the effects of age on counterregulatory responses to hypoglycemia (among nondiabetic individuals). In these studies, where the mean age of the older groups was markedly older than our cohort (age 60–70s), they found modest ( 55 ) or no ( 56 ) differences in counterregulatory responses to hypoglycemia.

It is also noteworthy that increased age and duration of diabetes may be associated with cerebrovascular dysfunction. Increased presence of cerebral small vessel disease such as white matter hyperintensities and lacunes have been reported among individuals with T1DM (mean age 50 years) ( 57 , 58 ) however, other studies among older T1DM patients (mean age

60 years and with known microvascular complications) ( 59 ) have reported no significant differences in white matter lesions or microinfarcts compared with control subjects. While we cannot exclude the possibility that occult cerebrovascular disease may also contribute to the differences observed in the T1DM-Unaware individuals, this appears less likely given our participants had well-controlled diabetes, had no history of cerebrovascular disease or cardiovascular disease, and were significantly younger (mean age 30 and 40 years for T1DM-Aware and -Unaware, respectively) than the groups reported in the literature.

Finally, even though our study includes larger numbers of T1DM-Aware and T1DM-Unaware participants than prior fMRI-based studies investigating hypoglycemia unawareness, our sample sizes remain a limitation. To minimize the risk of false positives, we used a PAG-value threshold of less than 0.001 ( 16 ). Currently, best practice guidelines for conducting fMRI based studies typically recommend at least 20 subjects per group to minimize false positives ( 60 ) however, these recommendations may not be directly applicable to studies among relatively rare disease groups such as individuals with T1DM and hypoglycemia unawareness or in study designs using highly controlled physiologic manipulations such as in a 2-step euglycemic-hypoglycemic clamp where individuals are compared to themselves at 2 well-defined, but different states.

In conclusion, the current study highlights the differential CNS responses to mild hypoglycemia among individuals with T1DM and preserved or diminished hypoglycemia awareness. Our findings suggest that although T1DM-Aware individuals no longer exhibit hypoglycemia-induced changes in reward and motivation brain regions (striatum), they have developed compensatory increases in activity in regions associated with attention (i.e., angular gyrus), which may be a protective adaptive mechanism to help maintain an appropriate response to falling glucose levels. However, T1DM patients with hypoglycemia unawareness fail to respond acutely to mild hypoglycemia in cortico-striatal and fronto-parietal brain regions. Taken together with the blunted counterregulatory hormone and subjective hypoglycemia symptom responses seen among these individuals, these CNS changes most likely play an important role in causing the inability of T1DM patients with hypoglycemia unawareness to detect and respond appropriately to falling plasma glucose levels. These findings underscore the importance of future interventional studies to determine whether reduction of hypoglycemia frequency can restore these changes in regional brain responses.

Participants. Participants were recruited from the greater New Haven area as well as the Yale Diabetes Center. Inclusion criteria for all subjects included ages 18–60 years, BMI less than 30 kg/m 2 , and ability to read English. Inclusion criteria for individuals with T1DM included HbA1c less than 9% and duration of diabetes more than 5 years. Exclusion criteria included inability to enter the MRI, smoking, illicit drug or recent steroid use, known psychiatric or neurological disorders, active infection, malignancy, abnormal thyroid function, cerebrovascular disease, cardiovascular disease, hepatobiliary disease, weight change in the last 3 months, and pregnancy or breastfeeding.

Sixty-seven potential subjects were screened at the Yale New Haven Hospital Research Unit (HRU) from November 2013 through July 2016 with a screening history, electrocardiogram, physical examination, and laboratory testing at the HRU. Of the 67 subjects screened, 42 participants completed the study and were included in the final analysis (see CONSORT diagram showing the flow of participants in the study, Supplemental Figure 1). They were divided into the following 3 groups: 13 HCs (6 males/7 females, age 33 ± 11 years, BMI 24.1 ± 2.9 kg/m 2 , HbA1c 5.0% ± 0.3%), 16 T1DM-Aware (5 males/11 females, age 30 ± 8 years, BMI 23.2 ± 3.4 kg/m 2 , HbA1c 7.0% ± 0.8%), and 13 T1DM-Unaware (6 males/7 females, age 40 ± 12 years, BMI 26.8 ± 2.9 kg/m 2 , HbA1c 6.9% ± 0.6%). The Clarke score ( 14 ) was used to differentiate participants with hypoglycemia awareness versus unawareness. If the Clarke score was not classifiable (i.e., when individuals reported a score of 3 R [R = number of questions designated “reduced awareness”]), then the Gold ( 61 ) method was used to determine whether they had impaired hypoglycemia awareness.

Study protocol. All participants with T1DM were asked to wear a continuous glucose monitor (CGM) (Dexcom G4) 1 week prior to their scheduled MRI visit in order to monitor for antecedent hypoglycemia. If participants had any episodes of hypoglycemia (glucose < 70 mg/dl or a symptomatic episode requiring assistance) in the 5 days prior to MRI scanning, then the scans were postponed to a later date. On the day of the MRI, participants arrived to the HRU at 9 AM. All participants were instructed to eat breakfast as usual prior to arrival and those with diabetes were further instructed to bolus insulin as usual for breakfast. At 10 AM, all participants were provided with a standardized snack consisting of 41 grams of carbohydrate (turkey sandwich, apple, diet ginger ale) in order to neutralize feelings of hunger as previously described ( 5 ). Participants with diabetes were instructed to inject a bolus of insulin as per their home insulin-to-carbohydrate ratio. Intravenous catheters were placed in antecubital veins bilaterally: one for blood sampling and the other for insulin and glucose infusion. Participants were informed that their glucose levels would be reduced below normal using an insulin and glucose infusion, which could lead to symptoms of hypoglycemia. Participants were blinded to the timing of changes in glucose levels. Scanning began in the MRI center at 12 PM simultaneously with initiation of an insulin infusion at 2 milliunits/kg/h. Euglycemia (

90 mg/dl) was maintained for the first phase of the study, after which glucose was decreased into the mild hypoglycemia range (

60 mg/dl) (Figure 1A). BOLD images were acquired during euglycemia (between 45 and 60 minutes) and hypoglycemia (between 90 and 105 minutes) sessions. Participants completed a visual food task while BOLD images were collected, as described below. Throughout the MRI scan, blood was sampled for glucose every 5 minutes. Counterregulatory hormones (epinephrine, norepinephrine, glucagon, and cortisol) were sampled at 0, 30, 45, 60, 75, 90, and 105 minutes.

Biochemical analysis. Plasma glucose was measured enzymatically using glucose oxidase (YSI). Plasma-free insulin, leptin, ghrelin, and glucagon were measured by double-antibody radioimmunoassay (Millipore), as was plasma cortisol (MP Biomedicals). Plasma epinephrine and norepinephrine were measured by high-performance liquid chromatography (ESA).

Visual food cue task. The visual food cue task we used has been previously validated for fMRI ( 5 , 47 ). During each euglycemia and hypoglycemia session, we presented a total of 42 images (3 runs of 14 pictures [7 high-calorie food images, 7 non-food images] each). High-calorie food pictures included items such as hamburgers, pizza, ice cream, and chocolate as previously described ( 5 ). Seventy-five percent of the high-calorie foods were also high-carbohydrate foods. Non-food pictures consisted of objects such as buildings, books, and doors. Using an event-related design, images were shown for 6 seconds. Each picture was displayed only once and the order of pictures was counterbalanced and randomized within condition across participants. At the end of each trial, a fixation cross appeared with a jittered inter-trial interval (mean, 6 seconds range, 3–9 seconds), during which participants relaxed until the onset of the next trial, as previously described ( 5 ). This process was repeated for each of the 3 runs that were presented at both euglycemia and hypoglycemia.

Hypoglycemia symptom assessments. Participants were asked to verbally rate their sensation of hypoglycemic symptoms (unable to concentrate, blurry vision, anxiety, confusion, difficulty speaking, double vision, drowsiness, tiredness, hunger, weakness, sweating, trembling, warmness, heart racing) on a 7-point Likert scale (1 indicating “not at all” and 7 indicating “a lot”) based upon the Edinburgh hypoglycemia symptom score ( 15 ) at 3 separate time points during the study: baseline (prior to entering the scanner) and then once they had reached target glucose levels for euglycemia (at 30 minutes) and hypoglycemia (at 90 minutes).

Statistics. One-way analysis of variance (ANOVA) was used to determine whether there were statistical differences among the 3 groups for all demographic variables followed by Fisher’s least significant difference (LSD) test for pairwise comparisons if the overall test was statistically significant. Analysis of repeatedly measured variables such as plasma glucose was performed using the mixed-effects regression model method, taking into account both between-subject and within-subject correlations of repeated measures using a combination of prespecified compound symmetry covariance matrix and an autoregressive covariance matrix. Age, gender, and BMI were adjusted as covariates (i.e., as fixed effects). Subsequently, pair-wise comparisons at each time point were performed. Least square mean difference and its 95% confidence interval are reported as a measure of effect size. To assess changes in counterregulatory hormones, plasma hormone levels at euglycemia (45 and 60 minutes) and hormone levels at hypoglycemia (90 and 105 minutes) were averaged together and compared using paired t tests. All analyses were performed using SAS, version 9.4 and SPSS, version 22 (IBM). A 2-tailed PAG value of less than 0.05 was considered to be statistically significant. Unless otherwise stated, data are presented as the mean ± standard error of the mean (SEM).

Study approval. The protocol was approved by the Yale University School of Medicine Human Investigation Committee. All subjects provided informed, written consent before participation.

fMRI analysis. The digital data (Digital Imaging and Communication in Medicine [DICOM]) were converted to NIFTI using dcm2nii ( 62 ) and then the first 3 images were discarded from each functional run to enable the signal to achieve steady-state equilibrium between radio-frequency pulsing and relaxation leaving 271 images per slice per run for analysis. The data were motion corrected using SPM8 (www.fil.ion.ucl.ac.uk/spm/software/spm8), and they were discarded if linear motion was greater than 1.5 mm or rotation was greater than 2 degrees. Images were iteratively smoothed until the smoothness for any image had a full width half maximum of approximately 6 mm ( 63 ). For individual subject data analysis, GLM was used to determine the regions with changes in signal in response to the visual task (high-calorie food or non-food image) in each session. To consider potential variability in baseline fMRI signal, drift correction was included in the GLM with drift regressors used to remove the mean time course, linear, quadratic, and cubic trends for each run. To adjust for anatomical differences in each individual, the Yale Bio-Image Suite software package (http://www.bioimagesuite.org/) was used to calculate 2 linear and 1 nonlinear registration. These 3 registrations were concatenated and applied as 1 registration to bring the data into a common reference brain space. The Colin27 Brain in the Montreal Neurological Institute (MNI) space was used as the reference brain. For group-level data analysis, linear effects modeling using AFNI 3dLME (http://afni.nimh.nih.gov) was implemented with a 3 (group: HC, T1DM-Aware, T1DM-Unaware) × 2 (session: euglycemia, hypoglycemia) × 2 (task: high-calorie food and non-food) design, while covarying for age, duration of diabetes, and BMI using the LME modeling program 3dLME from AFNI (https://afni.nimh.nih.gov/LME). In this design, task and session were treated as the within-subjects fixed-effect factors and group as the between-subjects factor and subject as the random-effect factor. To correct for multiple comparisons, we used FWE correction determined by Monte Carlo simulation using the AFNI 3dClustSim version (16.3.05, October 2016) program. Results are shown at PAG less than 0.05 whole-brain FWE corrected with an initial PAG threshold of less than 0.001, as described previously ( 16 ).

JJH and R. Sherwin had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. JJH, DS, RTC, R. Sinha, and R. Sherwin conceived and designed the study. JJH, LP, DS, CS, MH, WL, and RBD acquired the data. CL, JJH, FD, WL, and MH performed statistical analyses. All authors analyzed and interpreted the data and contributed to writing the manuscript.

This study was supported in part by grants from the NIH R01DK020495 and P30 DK045735 (to R. Sherwin), K23DK109284 (to JJH), and K08AA023545 (to DS). The Yale Center for Clinical Investigation was supported by an NIH Clinical Translational Science Award (UL1 RR024139). We gratefully acknowledge the help of the Yale Core lab staff: Mikhail Smolgovsky, Irene Chernyak, Ralph Jacob, Doreen Nemeth, Maria Batsu, and Codruta Todeasa as well as the Yale HRU nurses and staff: Joanne Caprio-Adams, Gina Solomon, Anne O’Connor, Catherine Parmelee, Mary Scanlon, Lynda Knaggs, Carmen Galarza, Elizabeth O’Neal, Joyce Russell, Gayle Pietrogallo, and Cynthia Smith.

Role of funding source: The funding agencies had no role in the design and conduct of the study collection, management, analysis, and interpretation of the data or the preparation, review, or approval of the manuscript.

Conflict of interest: JJH and R. Sherwin report receipt of research support from Regeneron. RBD reports receipt of research support from Glaxo Smith Kline.


Design and Methods

In 2014, we launched the InHypo-DM study in Canada. The objectives of this mixed-methods study were: 1) to explore, using quantitative and qualitative methods, the psychosocial and situational factors that can facilitate or impede hypoglycemia self-management behaviors among people with diabetes, significant others of people with diabetes, and health care providers (HCPs) involved in their care, and 2) to improve our understanding of the frequency of hypoglycemia (nonsevere, nocturnal, and severe) in people with type 1 or type 2 diabetes at risk for hypoglycemia (31,38). This study focuses on the first stated objective. Specifically, the qualitative component of the InHypo-DM study used a descriptive qualitative approach (39). The present analysis focuses on the experience of hypoglycemia through the lens of people with type 1 or type 2 diabetes.

Participant Recruitment

A purposive sample was used to recruit participants from Southwestern Ontario through a local diabetes clinic and by posters placed in various locations (e.g., doctors’ offices, pharmacies, and shopping malls). We sought to attain a maximum variation sample (in terms of age, type of diabetes, sex, and age of onset). All participants had to have experienced at least one hypoglycemia event in the previous 12 months. Western University’s Review Board for Health Sciences Research Involving Human Subjects approved this study.

Data Collection

After obtaining participants’ informed consent, a 30- to 45-minute semi-structured interview was conducted with each participant. Examples of interview questions included, “How does experiencing a hypoglycemia event make you feel?” and “What makes you feel hopeful about managing hypoglycemia events?” Hypoglycemia was defined to participants as a low blood sugar (glucose) event, also sometimes referred to as “hypo.” The interviews, conducted by members of the research team in a location convenient to the participants, were audiotaped and transcribed verbatim. Data collection ceased after reaching saturation (i.e., when no new themes emerged).

Data Analysis

Data analysis was both iterative and interpretative, using individual and team analyses. In the initial phase of the analysis, four members of the research team independently reviewed each transcript to identify key concepts emerging from the data. The team then met to compare independent reviews, culminating in the development of the coding template, which evolved over the course of the analysis. NVivo 10 software (QSR International) was used for coding and organizing the data. After completing this phase, the team met to further synthesize and interpret the main themes, using the techniques of immersion and crystallization (40). Immersion involves researchers’ complete engagement in the data, which sensitizes them to the tone, range, mood, and context of the data during the analysis (40). Crystallization reflects the ultimate synthesis of the main themes, as expressed by participants. Throughout the analysis, the team identified exemplar quotes reflecting the main themes. In the Results section, the exemplar quotes are identified by type of diabetes (e.g., T1), sex of participant (e.g., F for female), and participant number.

Credibility and Trustworthiness

Credibility and trustworthiness of the data were enhanced through verbatim transcripts, field notes generated after each interview, and independent and team analyses. Reflexivity was essential during the analyses. Because the research team members came from different professional backgrounds (e.g., social work, family medicine, and epidemiology), team members reflected on the ways in which our own values and experiences shaped the interpretation and reporting of the data.

Final Sample

The final sample consisted of 16 participants, including 10 women (5 with type 1 and 5 with type 2 diabetes) and 6 men (3 with type 1 and 3 with type 2 diabetes). The mean time since diagnosis was 15 years among those with type 1 diabetes and 21 years among those with type 2 diabetes. The mean age was 40 years (range 22–64) among those with type 1 diabetes and 60 years (range 45–77) among those with type 2 diabetes. All had experienced more than one hypoglycemia event in the past year, ranging from nonsevere to severe.


Implications for Self-Management

Researchers studying the relationship between cognitive functioning and chronic disease typically have assumed that chronic disease causes cognitive impairment. However, cognition also may be a risk factor for outcomes in chronic conditions with high self-management demands. For example, there is evidence that lower cognitive ability precedes obesity (34) in children who later become obese. This concept of “reverse causality” provides a rationale for a novel approach to behavioral intervention based on individual cognitive risk factors and using cognitive compensatory strategies, prompts, and environmental modifications to improve patients’ adherence to self-management behaviors despite cognitive barriers.

Fluid Cognition Declines With Age and Is Related to Medical Self-Management

Fluid cognition is a broad descriptor of a diverse set of discrete cognitive skills, including executive functioning, working memory, prospective memory, episodic memory, mental flexibility, attention, and complex processing speed and is highly sensitive to the effects of normal aging (35). Many of these cognitive skills also have been linked to medication self-management among diverse populations, including those with HIV (36,37), MCI and dementia (38), and Parkinson’s disease (39).

Executive functioning is the most consistently cited cognitive domain in research focused on predicting instrumental activities of daily living in older adults (40) and neurological populations (41). Of note, longitudinal decline in executive functioning and memory is associated with concomittant decline in instrumental activities of daily living in older adults both with and without MCI (38). Typically, when evaluating cognition in older adults, researchers control for the effects of normal age-related cognitive decline. Although this is appropriate when diagnosing a pathological disease state, it may not be appropriate when determining risk for medical mismanagement. It is possible that even normal age-related decline, coupled with the high demands of managing type 1 diabetes, could result in self-management problems. It is therefore crucial to identify the level of absolute cognitive performance that increases risk for self-management problems, even within the normal range.

Cognitive Impairment Is a Risk Factor for Poor Diabetes Self-Management

Although data in adults with type 1 diabetes are scarce, cognitive performance in older adults is associated with performance on simulated cognitively demanding diabetes self-management tasks (42). There is also evidence that cognition predicts self-management ability in children with type 1 diabetes and adults with type 2 diabetes. McNally et al. (43) used structural equation modeling to demonstrate that treatment adherence mediated the relationship between executive functioning and glycemic control in their sample of youth with type 1 diabetes. The alternative model (that adherence led to glycemic control, which in turn led to executive dysfunction) was not supported by the data. There are also increasing data suggesting that cognitive performance predicts type 2 diabetes self-management (44–46). Most studies have focused on the important role of executive functioning (i.e., planning, problem-solving, and mental flexibility) in managing diabetes.

Prevention of hypoglycemic events is a key self-management task that may be affected by cognitive function. The ACCORD-MIND trial (47) in patients with type 2 diabetes found that cognitive performance at baseline predicted hypoglycemic episodes at the 20-month follow-up in those with no baseline hypoglycemia. In addition, this trial found that cognitive decline from baseline to 20 months was predictive of hypoglycemic episodes at 20 months for those patients who began the trial with average or lower cognitive ability. These data indicate that cognitive ability must cross a functional threshold to begin to affect self-management and hypoglycemia risk (Figure 1). In another longitudinal study in type 2 diabetes, lower cognition at baseline was associated with a twofold higher risk of incident severe hypoglycemia over the next 4 years, and previous hypoglycemia also was associated with steeper cognitive decline (30). Executive functioning, processing speed, and memory (i.e., fluid cognition) had the strongest associations with hypoglycemia. It is possible that those with declining cognition are less able to prevent, recognize, and treat hypoglycemia.

Hypothesized model linking cognitive decline, self-management, and severe hypoglycemia (SH) risk.


Blood Sugar Homeostasis

Your body is always trying to keep things balanced.

We refer to this as homeostasis. 22 Freddy D Jeanneteau, W Marcus Lambert, Naima Ismaili, Kevin G Bath, Francis S Lee, Michael J Garabedian, Moses V Chao. BDNF and glucocorticoids regulate corticotrophin-releasing hormone (CRH) homeostasis in the hypothalamus, Proc Natl Acad Sci U S A. 2012

Regarding blood sugar, your body wants to keep the optimal amount of glucose in the blood in a goldilocks zone. Not too much, not too little. 23 Alex Rafacho, Henrik Ortsäter, Angel Nadal, Ivan Quesada. Glucocorticoid treatment and endocrine pancreas function: implications for glucose homeostasis, insulin resistance and diabetes, J Endocrinol. 2014

There are hormones, insulin, and glucagon, excreted from the pancreas and control the flow of glucose in and out of your bloodstream.

However, these are not the only hormones affecting glucose in your blood.

Stress hormones like cortisol are also directing glucose in the blood.

Oddly enough, blood glucose is also dictating cortisol.

This interplay of glucose and hormones can have profound effects on your mood.

Understanding and ultimately working to optimize your hormones through blood sugar control can greatly improve your mental health, sharpen your focus, and boost overall cognitive abilities.


Link between hypoglycemic events in Type 1 diabetics and clinical anxiety? - biología

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When to See a Doctor

If you're not diabetic and you have symptoms of hypoglycemia, you should see your doctor right away,   even if you're able to get your symptoms to subside by consuming simple carbohydrates such as 4 ounces of juice or non-diet soda, a serving of jellybeans as detailed by the package, a banana, 8 ounces of milk, 1 tablespoon of honey or corn syrup, or 2 tablespoons of raisins.

Being hypoglycemic means that something else is going on and you need to find out what that is so it can be treated before your hypoglycemia becomes life-threatening. If you're still having symptoms after treating your low blood sugar with the above measures, go to the emergency room immediately.

If you're diabetic, you will most likely deal with hypoglycemia on occasion. If your blood sugar is below 70 mg/dl, try one of the remedies detailed above or take glucose tablets as directed by the package. As long as your blood sugar goes back to normal, you can resume your regular activities. However, if you've treated your hypoglycemia and your blood sugar remains low and/or you still have symptoms, it's time to contact your doctor as soon as possible.

You should also visit with your doctor right away if you have symptoms of nocturnal hypoglycemia and/or recurring episodes of hypoglycemia since these can turn into serious, potentially life-threatening, problems if they're not treated.

If you or a loved one have severe symptoms such as behavioral changes, confusion, visual changes, slurred speech, seizures, or unconsciousness, get emergency help.


Agradecimientos

My thanks to L. Warren, M. Kendall and the members of the HARPdoc user group (King’s College London, London, UK) for discussions about hypoglycaemia from the perspective of the people with diabetes. Also to my research colleagues in the Diabetes Research Group and Centre for Neuroimaging Sciences, both at King’s College London (London, UK), and my clinical colleagues and patients at King’s College Hospital NHS Foundation Trust, without whom much of the work reported here would not have occurred.

Author’s relationships and activities

SAA has served on advisory boards for NovoNordisk, Abbott UK and Roche and spoken at a meeting sponsored by Sanofi in the last 36 months.


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