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ObjectiveTo examine the association between prediagnostic plasma polyunsaturated fatty acids levels (PUFA) and amyotrophic lateral sclerosis (ALS).MethodsWe identified 275 individuals who developed ALS while enrolled in 5 US prospective cohorts, and randomly selected 2 controls, alive at the time of the case diagnosis, matched on cohort, birth year, sex, ethnicity, fasting status, and time of blood draw. We measured PUFA, expressed as percentages of total fatty acids, using gas liquid chromatography and used conditional logistic regression to estimate risk ratios (RR) and 95% confidence intervals (CI) for the association between PUFA and ALS.ResultsThere was no association between total, n-3, and n-6 PUFA, eicosapentaenoic acid, or docosapentaenoic acid levels and ALS. Higher plasma α-linolenic acid (ALA) in men was associated with lower risk of ALS in age- and matching factor-adjusted analyses (top vs bottom quartile: RR = 0.21 [95% CI 0.07, 0.58], p for trend = 0.004). In women, higher plasma arachidonic acid was associated with higher risk (top vs bottom quartile: RR = 1.65 [95% CI 0.99, 2.76], p for trend = 0.052). Multivariable adjustment, including correlated PUFA, did not change the findings for ALA and arachidonic acid. In men and women combined, higher plasma docosahexaenoic acid (DHA) was associated with higher risk of ALS (top vs bottom quartile: RR = 1.56 [95% CI 1.01, 2.41], p for trend = 0.054), but in multivariable models the association was only evident in men.ConclusionsThe majority of individual PUFAs were not associated with ALS. In men, ALA was inversely and DHA was positively related to risk of ALS, while in women arachidonic acid was positively related. These findings warrant confirmation in future studies.

ObjectiveTo identify prediagnostic plasma metabolomic biomarkers associated with amyotrophic lateral sclerosis (ALS).MethodsWe conducted a global metabolomic study using a nested case-control study design within 5 prospective cohorts and identified 275 individuals who developed ALS during follow-up. We profiled plasma metabolites using liquid chromatography-mass spectrometry and identified 404 known metabolites. We used conditional logistic regression to evaluate the associations between metabolites and ALS risk. Further, we used machine learning analyses to determine whether the prediagnostic metabolomic profile could discriminate ALS cases from controls.ResultsA total of 31 out of 404 identified metabolites were associated with ALS risk (p < 0.05). We observed inverse associations (n = 27) with plasma levels of diacylglycerides and triacylglycerides, urate, purine nucleosides, and some organic acids and derivatives, while we found positive associations for a cholesteryl ester, 2 phosphatidylcholines, and a sphingomyelin. The number of significant associations increased to 67 (63 inverse) in analyses restricted to cases with blood samples collected within 5 years of onset. None of these associations remained significant after multiple comparison adjustment. Further, we were not able to reliably distinguish individuals who became cases from controls based on their metabolomic profile using partial least squares discriminant analysis, elastic net regression, random forest, support vector machine, or weighted correlation network analyses.ConclusionsAlthough the metabolomic profile in blood samples collected years before ALS diagnosis did not reliably separate presymptomatic ALS cases from controls, our results suggest that ALS is preceded by a broad, but poorly defined, metabolic dysregulation years before the disease onset.

Human microbiome science has advanced rapidly and reached a scale at which basic biology, clinical translation and population health are increasingly integrated. It is thus now possible for public health researchers, practitioners and policymakers to take specific action leveraging current and future microbiome-based opportunities and best practices. Here we provide an outline of considerations for research, education, interpretation and scientific communication concerning the human microbiome and public health. This includes guidelines for population-scale microbiome study design; necessary physical platforms and analysis methods; integration into public health areas such as epidemiology, nutrition, chronic disease, and global and environmental health; entrepreneurship and technology transfer; and educational curricula. Particularly in the near future, there are both opportunities for the incorporation of microbiome-based technologies into public health practice, and a growing need for policymaking and regulation around related areas such as prebiotic and probiotic supplements, novel live-cell therapies and fecal microbiota transplants. Microbiome science is fast advancing and its careful integration into public health is detailed in this Perspective., Author(s): Jeremy E. Wilkinson [sup.1] [sup.2] , Eric A. Franzosa [sup.1] [sup.2] [sup.3] , Christine Everett [sup.1] [sup.4] , Chengchen Li [sup.1] [sup.2] , Sena Bae [sup.1] [sup.7] , Isa [...]

Objective: Prior studies on the gut microbiome in Parkinson's disease (PD) have yielded conflicting results, and few studies have focused on prodromal (premotor) PD or used shotgun metagenomic profiling to assess microbial functional potential. We conducted a nested case–control study within 2 large epidemiological cohorts to examine the role of the gut microbiome in PD. Methods: We profiled the fecal metagenomes of 420 participants in the Nurses' Health Study and the Health Professionals Follow‐up Study with recent onset PD (N = 75), with features of prodromal PD (N = 101), controls with constipation (N = 113), and healthy controls (N = 131) to identify microbial taxonomic and functional features associated with PD and features suggestive of prodromal PD. Omnibus and feature‐wise analyses identified bacterial species and pathways associated with prodromal and recently onset PD. Results: We observed depletion of several strict anaerobes associated with reduced inflammation among participants with PD or features of prodromal PD. A microbiome‐based classifier had moderate accuracy (area under the curve [AUC] = 0.76 for species and 0.74 for pathways) to discriminate between recently onset PD cases and controls. These taxonomic shifts corresponded with functional shifts indicative of carbohydrate source preference. Similar, but less marked, changes were observed in participants with features of prodromal PD, in both microbial features and functions. Interpretation: PD and features of prodromal PD were associated with similar changes in the gut microbiome. These findings suggest that changes in the microbiome could represent novel biomarkers for the earliest phases of PD. ANN NEUROL 2023;94:486–501 [ABSTRACT FROM AUTHOR]

Background: Cognitive deficits can be present in the prodromal phase of Parkinson's disease (PD). Subjective cognitive decline (SCD) may contribute to identifying individuals with prodromal PD. Objective: The objective of this study was to examine whether SCD is more likely to be present in women with features suggestive of prodromal PD compared with women without these features. Methods: The study population comprised 12,427 women from the Nurses' Health Study selected to investigate prodromal PD. Prodromal and risk markers of PD were assessed via self‐administered questionnaires. We evaluated the association of hyposmia, constipation, and probable rapid eye movement sleep behavior disorder, three major features of prodromal PD, with SCD, adjusting for age, education, body mass index, physical activity, smoking, alcohol, caffeine intake, and depression. We also explored whether SCD was associated with the probability of prodromal PD and conducted additional analyses using data from neurocognitive tests. Results: Women experiencing the three examined nonmotor features had the worst mean SCD score and the highest odds of poor subjective cognition (odds ratio [OR] = 1.78; 95% confidence interval [CI], 1.29–2.47). This association persisted when women with objective cognitive deficits were excluded from analyses. SCD was also more common in women with a probability of prodromal PD ≥0.80, particularly among those aged younger than 75 years (OR of poor subjective cognition = 6.57 [95% CI, 2.43–17.77]). These observations were consistent with the results from analyses using neurocognitive tests, where a worse global cognitive performance was observed among women with three features. Conclusions: Our study suggests that self‐perceived cognitive decline can be present during the prodromal phase of PD. © 2023 International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Objective: Limiting SFA intake may minimise the risk of CHD. However, such reduction often leads to increased intake of carbohydrates. We aimed to evaluate associations and the interplay of carbohydrate and SFA intake on CHD risk.Design: Prospective cohort study.Setting: We followed participants in the Hordaland Health Study, Norway from 1997-1999 through 2009. Information on carbohydrate and SFA intake was obtained from a FFQ and analysed as continuous and categorical (quartiles) variables. Multivariable Cox regression estimated hazard ratios (HR) and 95 % CI. Theoretical substitution analyses modelled the substitution of carbohydrates with other nutrients. CHD was defined as fatal or non-fatal CHD (ICD9 codes 410-414 and ICD10 codes I20-I25).Participants: 2995 men and women, aged 46-49 years.Results: Adjusting for age, sex, energy intake, physical activity and smoking, SFA was associated with lower risk (HRQ4 v. Q1 0·44, 95 % CI 0·26, 0·76, Ptrend = 0·002). For carbohydrates, the opposite pattern was observed (HRQ4 v. Q1 2·10, 95 % CI 1·22, 3·63, Ptrend = 0·003). SFA from cheese was associated with lower CHD risk (HRQ4 v. Q1 0·44, 95 % CI 0·24, 0·83, Ptrend = 0·006), while there were no associations between SFA from other food items and CHD. A 5 E% substitution of carbohydrates with total fat, but not SFA, was associated with lower CHD risk (HR 0·75, 95 % CI 0·62, 0·90).Conclusions: Higher intake of predominantly high glycaemic carbohydrates and lower intake of SFA, specifically lower intake from cheese, were associated with higher CHD risk. Substituting carbohydrates with total fat, but not SFA, was associated with significantly lower risk of CHD. [ABSTRACT FROM AUTHOR]

Background: It is unknown how individuals with multiple sclerosis (MS) age compared to unaffected peers. Objectives: The objective of the study is to describe the impact of MS on health and functioning in aging women. Methods: We used 10-item Physical Functioning Scale (PF10) scores (from the Short Form-36 (SF-36)) and other indicators of general, physical, mental health, and memory collected repeatedly over 25 years with self-administered questionnaires among participants in the Nurses' Health Study (n = 121,700 recruited at ages 30–55) and Nurses' Health Study II (n = 116,429 recruited at ages 25–42) to compare women with MS (n = 733) to unaffected peers in their health and disability, and describe/quantify the burden of aging with MS. Results: Women with MS had a consistently lower PF10 by 0.9–1.7 standard deviations with greater overall variability than unaffected women. PF10-scores gradually decreased with increasing age in both groups, but MS cases declined 3–4 times faster in midlife, while decline was similar in old age. The physical function score of 45-year-old women with MS was comparable to that of 75-year-old unaffected women; 70-year-old women with MS scored similarly to 85-year-old unaffected women. MS cases also reported worse health/more disability throughout adulthood on the other indicators. Conclusion: The age-related decline in physical health is accelerated by 15–30 years in MS patients compared to unaffected peers. [ABSTRACT FROM AUTHOR]