Introduction: Increasing evidence suggests a role for the gut microbiome in central nervous system disorders and specific role for the gut-brain axis in neurodegeneration. Bile acids (BA), products of cholesterol metabolism and clearance, are produced in the liver and are further metabolized by gut bacteria. They have major regulatory and signaling functions and seem dysregulated in Alzheimer disease (AD). Methods: Serum levels of 15 primary and secondary BAs and their conjugated forms were measured in 1,464 subjects including 370 cognitively normal older adults (CN), 284 with early mild cognitive impairment (MCI), 505 with late MCI, and 305 AD cases enrolled in the AD Neuroimaging Initiative. We assessed associations of BA profiles including selected ratios with diagnosis, cognition, and AD-related genetic variants, adjusting for cofounders and multiple testing. Results: In AD compared to CN, we observed significantly lower serum concentrations of a primary BA (cholic acid CA) and increased levels of the bacterially produced, secondary BA, deoxycholic acid (DCA), and its glycine and taurine conjugated forms. An increased ratio of DCA:CA, which reflects 7α-dehydroxylation of CA by gut bacteria, strongly associated with cognitive decline, a finding replicated in serum and brain samples in the Rush Religious Orders and Memory and Aging Project. Several genetic variants in immune response related genes implicated in AD showed associations with BA profiles. Conclusion: We report for the first time an association between altered BA profile, genetic variants implicated in AD and cognitive changes in disease using a large multicenter study. These findings warrant further investigation of gut dysbiosis and possible role of gut liver brain axis in the pathogenesis of AD.

44Across a large variety of Mendelian disorders, ~50-75% of patients do not receive a 45 genetic diagnosis by whole exome sequencing indicative of underlying disease-causing 46 variants in non-coding regions. In contrast, whole genome sequencing facilitates the 47 discovery of all genetic variants, but their sizeable number, coupled with a poor 48 understanding of the non-coding genome, makes their prioritization challenging. Here, we 49 demonstrate the power of transcriptome sequencing to provide a confirmed genetic 50 diagnosis for 10% (5 of 48) of undiagnosed mitochondrial disease patients and identify 51 strong candidate genes for patients remaining without diagnosis. We found a median of 1 52 aberrantly expressed gene, 5 aberrant splicing events, and 6 mono-allelically expressed 53 rare variants in patient-derived fibroblasts and established disease-causing roles for each 54 kind. Private exons often arose from sites that are weakly spliced in other individuals, 55providing an important clue for future variant prioritization. One such intronic exon-56 creating variant was found in three unrelated families in the complex I assembly factor 57 TIMMDC1, which we consequently established as a novel disease-associated gene. In 58 conclusion, our study expands the diagnostic tools for detecting non-exonic variants of 59Mendelian disorders and provides examples of intronic loss-of-function variants with 60 pathological relevance. 61Despite the revolutionizing impact of whole exome sequencing (WES) on the molecular 62 genetics of Mendelian disorders, ~50-75% of the patients do not receive a genetic diagnosis after 63 WES [1][2][3][4][5][6] . The disease-causing variants might be detected by WES but remain as variants of 64 unknown significance (VUS, Methods) or they are missed due to the inability to prioritize them. 65Many of these VUS are synonymous or non-coding variants that may affect RNA abundance or 66 isoform but cannot be prioritized due to the poor understanding of regulatory sequence to date 67 compared to coding sequence. Furthermore, WES covers only the 2% exonic regions of the 68 genome. Accordingly, it is mostly blind to regulatory variants in non-coding regions that could 69 affect RNA sequence and abundance. While the limitation of genome coverage is overcome by 70 whole genome sequencing (WGS), prioritization and interpretation of variants identified by 71 WGS is in turn limited by their amount [7][8][9] . 72With RNA sequencing (RNA-seq), limitations of the sole genetic information can be 73 complemented by directly probing variations in RNA abundance and in RNA sequence, 74 including allele-specific expression and splice isoforms. At least three extreme situations can be 75 directly interpreted to prioritize candidate disease-causing genes for a rare disorder. First, the 76 expression level of a gene can lie outside its physiological range. Genes with expression outside 77 their physical range can be identified as expression outliers, often using a stringent cutoff on 78 expression variat...

Detangling gene-disease connections Many diseases are at least partially due to genetic causes that are not always understood or targetable with specific treatments. To provide insight into the biology of various human diseases as well as potential leads for therapeutic development, Pietzner et al . undertook detailed, genome-wide proteogenomic mapping. The authors analyzed thousands of connections between potential disease-associated mutations, specific proteins, and medical conditions, thereby providing a detailed map for use by future researchers. They also supplied some examples in which they applied their approach to medical contexts as varied as connective tissue disorders, gallstones, and COVID-19 infections, sometimes even identifying single genes that play roles in multiple clinical scenarios. —YN

In cross-platform analyses of 174 metabolites we identify 499 associations (p<4.9×10 -10 ) characterized by pleiotropy, allelic heterogeneity, large and non-linear effects, and enrichment for nonsynonymous variation. We identify a signal at GLP2R (p.Asp470Asn) shared between higher citrulline levels, body mass index, fasting glucose-dependent insulinotropic peptide and type 2 diabetes, with beta-arrestin signalling as the underlying mechanism. Genetically-higher serine levels are shown to reduce the likelihood (by 95%) and predict development of macular telangiectasia type 2, a rare degenerative retinal disease. Integration of genomic and small molecule data across platforms enables discovery of regulators of human metabolism and translation into clinical insights. M.P. was supported by a fellowship from the German Research Foundation (DFG PI 1446/2-1). C.O. was founded by an early career fellowship at Homerton College, University of Cambridge. L. B. L. W.

Late-onset Alzheimer's disease (AD) can, in part, be considered a metabolic disease. Besides age, female sex and APOE ε4 genotype represent strong risk factors for AD that also give rise to large metabolic differences. We systematically investigated group-specific metabolic alterations by conducting stratified association analyses of 139 serum metabolites in 1,517 individuals from the AD Neuroimaging Initiative with AD biomarkers. We observed substantial sex differences in effects of 15 metabolites with partially overlapping differences for APOE ε4 status groups. Several group-specific metabolic alterations were not observed in unstratified analyses using sex and APOE ε4 as covariates. Combined stratification revealed further subgroup-specific metabolic effects limited to APOE ε4+ females. The observed metabolic alterations suggest that females experience greater impairment of mitochondrial energy production than males. Dissecting metabolic heterogeneity in AD pathogenesis can therefore enable grading the biomedical relevance for specific pathways within specific subgroups, guiding the way to personalized medicine.

Key Points Question Are liver function markers associated with cognition and the “A/T/N” (amyloid, tau, and neurodegeneration) biomarkers for Alzheimer disease? Findings In this cohort study of 1581 older adults, elevated aspartate aminotransferase to alanine aminotransferase ratios were associated with diagnosis of Alzheimer disease, poor cognition, lower cerebrospinal fluid levels of amyloid-β 1-42, increased amyloid-β deposition, higher cerebrospinal fluid levels of phosphorylated tau and total tau, and reduced brain glucose metabolism. Lower levels of alanine aminotransferase were associated with increased amyloid-β deposition, reduced brain glucose metabolism, greater brain atrophy, diagnosis of Alzheimer disease, and poor cognition. Meaning Consistent associations of serum-based liver function markers with Alzheimer disease biomarkers highlight the involvement of metabolic disturbances in the pathophysiology of Alzheimer disease.

Background: Exercise changes the concentrations of many metabolites, which are small molecules (< 1.5 kDa) metabolized by the reactions of human metabolism. In recent years, especially mass spectrometry-based metabolomics methods have allowed researchers to measure up to hundreds of metabolites in a single sample in a non-biased fashion. To summarize human exercise metabolomics studies to date, we conducted a systematic review that reports the results of experiments that found metabolite concentrations changes after a bout of human endurance or resistance exercise.Methods: We carried out a systematic review following PRISMA guidelines and searched for human metabolomics studies that report metabolite concentrations before and within 24 h after endurance or resistance exercise in blood, urine, or sweat. We then displayed metabolites that significantly changed their concentration in at least two experiments. Results: Twenty-seven studies and 57 experiments matched our search criteria and were analyzed. Within these studies, 196 metabolites changed their concentration significantly within 24 h after exercise in at least two experiments. Human biofluids contain mainly unphosphorylated metabolites as the phosphorylation of metabolites such as ATP, glycolytic intermediates, or nucleotides traps these metabolites within cells. Lactate, pyruvate, TCA cycle intermediates, fatty acids, acylcarnitines, and ketone bodies all typically increase after exercise, whereas bile acids decrease. In contrast, the concentrations of proteinogenic and non-proteinogenic amino acids change in different directions.Conclusion: Across different exercise modes and in different subjects, exercise often consistently changes the average concentrations of metabolites that belong to energy metabolism and other branches of metabolism. This dataset is a useful resource for those that wish to study human exercise metabolism.

Introduction: Bile acids (BAs) are the end products of cholesterol metabolism produced by human and gut microbiome co-metabolism. Recent evidence suggests gut microbiota influence pathological features of Alzheimer’s disease (AD) including neuroinflammation and amyloid-β deposition. Method: Serum levels of 20 primary and secondary BA metabolites from the AD Neuroimaging Initiative (n=1562) were measured using targeted metabolomic profiling. We assessed the association of BAs with the “A/T/N” (Amyloid, Tau and Neurodegeneration) biomarkers for AD: CSF biomarkers, atrophy (MRI), and brain glucose metabolism ([18F]FDG-PET). Results: Of 23 BA and relevant calculated ratios after quality control procedures, three BA signatures were associated with CSF Aβ1–42 (“A”) and three with CSF p-tau181 (“T”) (corrected p<0.05). Furthermore, three, twelve, and fourteen BA signatures were associated with CSF t-tau, glucose metabolism, and atrophy (“N”), respectively (corrected p<0.05). Conclusion: This is the first study to show serum-based BA metabolites are associated with “A/T/N” AD biomarkers, providing further support for a role of BA pathways in AD pathophysiology. Prospective clinical observations and validation in model systems are needed to assess causality and specific mechanisms underlying this association.