Longitudinal study of narcolepsy symptoms in first, second, and third-degree relatives of simplex and multiplex narcolepsy families

Differential characteristics of repeated polysomnography and multiple sleep latency test parameters in narcolepsy type 1 and type 2 patients: a longitudinal retrospective study

PURPOSE

Narcolepsy is a chronic disorder and its phenotype is dichotomized into narcolepsy type 1 (NT1) and narcolepsy type 2 (NT2). The clinical course and pathophysiological mechanisms of these two clinical entities and their differences are not adequately defined. This study aimed to explore the differential longitudinal patterns of polysomnography (PSG) and multiple sleep latency test (MSLT) in NT1 and NT2.

METHODS

In this retrospective study demographic characteristics, PSG, and MSLT parameters at baseline and follow-up were compared between NT1 and NT2 patients. Patients with both follow-up MSLT and PSG were selected for sub-group analysis. Baseline and follow-up MSLT and PSG parameters were compared.

RESULTS

Of 55 patients with narcolepsy, mean follow-up periods were 7.4 ± 3.5 years for NT1 and 5.5 ± 2.9 for NT2. Demographic data showed increased body mass index and prevalence of sleep paralysis in NT1. Baseline PSG characteristics between NT1 and NT2 showed decreased sleep latency (p = 0.016) and REM latency (p = 0.046) in NT1 group when compared with NT2. Nocturnal SOREMP on PSG was more prevalent in NT1 (p = 0.017), and half of NT2 patients with nocturnal SOREMP on PSG changed their diagnoses to NT1. On follow-up PSG, NT1 displayed reductions in sleep stage N2 (p = 0.006) and N3 (p = 0.048), while wake after sleep onset (WASO) (p = 0.023) and apnea-hypopnea index (AHI) (p = 0.007) were significantly increased.

CONCLUSION

Differential MSLT and PSG characteristics of NT1 and NT2 in at baseline and follow-up indicate that NT1 and NT2 are distinct disease phenotypes, and that they present with a contrasting course of disease.

Presence of high-risk HLA genotype is the most important individual risk factor for coeliac disease among at-risk relatives

BACKGROUND

Family screening has been advocated as a means to reduce the major underdiagnosis of coeliac disease. However, the precise risk of the disease in relatives and the impact of patient- and relative-related individual factors remain obscure.

AIMS

To investigate the individual risk of coeliac disease among patients' relatives.

METHODS

Altogether 2943 relatives of 624 index patients were assessed for the presence of previous coeliac disease diagnosis, or were screened for the disease. Coeliac disease-associated human leucocyte antigen (HLA) genotype was determined from all participants. The association between individual factors and new screening positivity was assessed by logistic regression.

RESULTS

There were 229 previously diagnosed non-index relatives with coeliac disease and 2714 non-affected (2067 first-degree, 647 more distant) relatives. Of these 2714 relatives, 129 (4.8%) were screening-positive (first-degree 5.1%, second-degree 3.6%, more distant 3.5%). The combined prevalence of the previously diagnosed and now detected cases in relatives was 12.2% (6.3% clinically detected, 5.9% screen-detected). In univariate analysis, age <18 years at diagnosis (odds ratio 1.60, 95% CI 1.04-2.45) in index, and age 41-60 years (1.73, 1.10-2.73), being a sibling (1.65, 1.06-2.59) and having the high-risk genotype (3.22, 2.01-5.15 DQ2.5/2.5 or DQ2.5/2.2 vs other risk alleles) in relatives were associated with screening positivity. Only high-risk HLA remained significant (2.94, 1.80-4.78) in multivariable analysis.

CONCLUSIONS

Unrecognised coeliac disease was common among at-risk relatives even in a country with an active case-finding policy, and also in relatives more distant than first-degree. The presence of a high-risk genotype was the most important predictor for screening positivity. ClinicalTrials.gov identifier NCT03136731.

Environmental open-source data sets and sleep-wake rhythms of populations: an overview

OBJECTIVE/BACKGROUND

In recent decades, the epidemiology of sleep disorders has mainly consisted of interviewing subjects through validated questionnaires; more recently, this has been done by assessing total sleep time (TST) per 24 h via sleep logs or connected devices. Thus, a vast amount of data has helped demonstrate the decline of TST in most countries. Nonetheless, we believe from a societal and environmental point of view that sleep researchers have largely overlooked a wide-open field of data that may help us to better understand and describe global sleep wake rhythms (SWR), eg, data regarding the sleep environment.

METHODS

Based on recent literature, we identified several environmental and societal fields that may have an effect on SWR. With the help of an expert panel, we selected the five most pertinent fields with multiple open-source data sets that may have an impact on human SWR. Then, we performed web-based research and proposed open-field data sets for each field, all of which are open to researchers and possibly scientifically associated with SWR.

RESULTS

The open fields relevant to the environment that we selected were noise, light pollution, and radio frequencies. The two societal fields were transportation and internet use. The evolution of most of these fields in recent decades may explain (even partially) the decline in TST. Importantly, the open data sets in each field are widely available to sleep researchers.

CONCLUSIONS

SWR must be assessed not only by patient accounts, but also in terms of the evolution of environmental cues.