Plasma proteome profiling reveals metabolic and immunologic differences between Anorexia Nervosa subtypes.

AIMS/HYPOTHESIS: Anorexia Nervosa (AN) is a severe psychiatric disorder of an unknown etiology with a crude mortality rate of about 5 % per decade, making it one of the deadliest of all psychiatric illnesses. AN is broadly classified into two main subtypes, restricting and binge/purging disorder. Despite extensive research efforts during several decades, the underlying pathophysiology of AN remains poorly understood. In this study, we aimed to identify novel protein biomarkers for AN by performing a proteomics analysis of fasting plasma samples from 78 females with AN (57 restrictive and 21 binge/purge type) and 70 healthy controls. METHODS: Using state-of-the-art mass spectrometry-based proteomics technology in conjunction with an advanced bioinformatics pipeline, we quantify >500 plasma proteins. RESULTS: Differential expression analysis and correlation of proteomics data with clinical variables led to identification of a panel of novel protein biomarkers with potential pathophysiological significance for AN. Our findings demonstrate evidence of a humoral immune system response, altered lipid metabolism and potential alteration of plasma cells in AN patients. Additionally, we stratified AN patients based on the quantified proteins and suggest a potential autoimmune nature in the restrictive subtype of AN. CONCLUSIONS/INTERPRETATION: In summary, on top of biomarkers of AN subtypes, this study provides a comprehensive map of plasma proteins that constitute a resource for further studies of the pathophysiology of AN.

Associations between short-chain fatty acid levels and mood disorder symptoms: a systematic review.

Background: Available evidence points to a possible role of Short Chain Fatty Acids (SCFAs) in mood disorders. This is the first systematic review to map the associations between SCFA levels and mood disorder symptoms.Methods: Following the PRISMA guidelines, the databases PubMed, Embase, and PsycINFO were searched for studies that assessed SCFA levels in human populations with mood disorder symptoms, or animal models of mood disorder. Risk of bias was assessed by the Strengthening of Reporting of Observational Studies in Epidemiology (STROBE) checklist.Results: 19 studies were included and could be divided into animal (n=8) and human studies (n=11), with the animal studies including 166 animals and 100 controls, and the human studies including 662 participants and 330 controls. The studies were characterized by heterogeneity and methodological challenges on multiple parameters, limiting the validity and transferability of findings. Notably, only two of the clinical studies assessed the presence of mood disorder with diagnostic criteria, and no studies of mania or bipolar disorder met the inclusion criteria.Discussion: Despite significant methodological limitations, associations between SCFA levels and depressive symptoms were reported in most of the studies. However, the direction of these associations and the specific SCFAs identified varied. The quantification of SCFA levels in mood disorders is an emerging yet sparsely studied research field. Although there is some evidence suggesting a link between SCFAs and depressive symptoms, the directionality of effects and mechanisms are unclear and the relation to manic symptoms is uninvestigated.

Alteration of Gut Microbiome in Patients With Schizophrenia Indicates Links Between Bacterial Tyrosine Biosynthesis and Cognitive Dysfunction.

Background: Schizophrenia (SCZ) is a heterogeneous neuropsychiatric disorder for which current treatment has insufficient efficacy and severe adverse effects. The modifiable gut microbiome might be a potential target for intervention to improve neurobiological functions through the gut-microbiome-brain axis. Methods: In this case-control study, gut microbiota of 132 patients with SCZ and increased waist circumference were compared with gut microbiota of two age- and sex-matched control groups, composed of 132 healthy individuals and 132 individuals with metabolic syndrome. Shotgun sequencing was used to characterize fecal samples at the taxonomic and functional levels. Cognition of the patients with SCZ was evaluated using the Brief Assessment of Cognition instrument. Results: SCZ gut microbiota differed significantly from those of healthy control subjects and individuals with metabolic syndrome in terms of richness and global composition. SCZ gut microbiota were notably enriched in Flavonifractor plautii, Collinsella aerofaciens, Bilophila wadsworthia, and Sellimonas intestinalis, while depleted in Faecalibacterium prausnitzii, Ruminococcus lactaris, Ruminococcus bicirculans, and Veillonella rogosae. Functional potential of the gut microbiota accounted for 11% of cognition variability. In particular, the bacterial functional module for synthesizing tyrosine, a precursor for dopamine, was in SCZ cases positively associated with cognitive score (ρ = 0.34, q ≤ .1). Conclusions: Overall, this study shows that the gut microbiome of patients with SCZ differs greatly from that of healthy control subjects or individuals with metabolic syndrome. Cognitive function of patients with SCZ is associated with the potential for gut bacterial biosynthesis of tyrosine, a precursor for dopamine, suggesting that gut microbiota might be an intervention target for alleviation of cognitive dysfunction in SCZ.

The gut microbiota contributes to the pathogenesis of anorexia nervosa in humans and mice.

Anorexia nervosa (AN) is an eating disorder with a high mortality. About 95% of cases are women and it has a population prevalence of about 1%, but evidence-based treatment is lacking. The pathogenesis of AN probably involves genetics and various environmental factors, and an altered gut microbiota has been observed in individuals with AN using amplicon sequencing and relatively small cohorts. Here we investigated whether a disrupted gut microbiota contributes to AN pathogenesis. Shotgun metagenomics and metabolomics were performed on faecal and serum samples, respectively, from a cohort of 77 females with AN and 70 healthy females. Multiple bacterial taxa (for example, Clostridium species) were altered in AN and correlated with estimates of eating behaviour and mental health. The gut virome was also altered in AN including a reduction in viral-bacterial interactions. Bacterial functional modules associated with the degradation of neurotransmitters were enriched in AN and various structural variants in bacteria were linked to metabolic features of AN. Serum metabolomics revealed an increase in metabolites associated with reduced food intake (for example, indole-3-propionic acid). Causal inference analyses implied that serum bacterial metabolites are potentially mediating the impact of an altered gut microbiota on AN behaviour. Further, we performed faecal microbiota transplantation from AN cases to germ-free mice under energy-restricted feeding to mirror AN eating behaviour. We found that the reduced weight gain and induced hypothalamic and adipose tissue gene expression were related to aberrant energy metabolism and eating behaviour. Our 'omics' and mechanistic studies imply that a disruptive gut microbiome may contribute to AN pathogenesis.

Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug-omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug-drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities.

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study.

The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired ß cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments.

Trans-ethnic gut microbiota signatures of type 2 diabetes in Denmark and India.

BACKGROUND: Type 2 diabetes (T2D), a multifactorial disease influenced by host genetics and environmental factors, is the most common endocrine disease. Several studies have shown that the gut microbiota as a close-up environmental mediator influences host physiology including metabolism. The aim of the present study is to examine the compositional and functional potential of the gut microbiota across individuals from Denmark and South India with a focus on T2D. Many earlier studies have investigated the microbiome aspects of T2D, and it has also been anticipated that such microbial associations would be dependent on diet and ethnic origin. However, there has been no large scale trans-ethnic microbiome study earlier in this direction aimed at evaluating any "universal" microbiome signature of T2D. METHODS: 16S ribosomal RNA gene amplicon sequencing was performed on stool samples from 279 Danish and 294 Indian study participants. Any differences between the gut microbiota of both populations were explored using diversity measures and negative binomial Wald tests. Study samples were stratified to discover global and country-specific microbial signatures for T2D and treatment with the anti-hyperglycemic drug, metformin. To identify taxonomical and functional signatures of the gut microbiota for T2D and metformin treatment, we used alpha and beta diversity measures and differential abundances analysis, comparing metformin-naive T2D patients, metformin-treated T2D patients, and normoglycemic individuals. RESULTS: Overall, the gut microbial communities of Danes and Indians are compositionally very different. By analyzing the combined study materials, we identify microbial taxonomic and functional signatures for T2D and metformin treatment. T2D patients have an increased relative abundance of two operational taxonomic units (OTUs) from the Lachnospiraceae family, and a decreased abundance of Subdoligranulum and Butyricicoccus. Studying each population per se, we identified T2D-related microbial changes at the taxonomic level within the Danish population only. Alpha diversity indices show that there is no significant difference between normoglycemic individuals and metformin-naive T2D patients, whereas microbial richness is significantly decreased in metformin-treated T2D patients compared to metformin-naive T2D patients and normoglycemic individuals. Enrichment of two OTUs from Bacteroides and depletion of Faecalibacterium constitute a trans-ethnic signature of metformin treatment. CONCLUSIONS: We demonstrate major compositional differences of the gut microbiota between Danish and South Indian individuals, some of which may relate to differences in ethnicity, lifestyle, and demography. By comparing metformin-naive T2D patients and normoglycemic individuals, we identify T2D-related microbiota changes in the Danish and Indian study samples. In the present trans-ethnic study, we confirm that metformin changes the taxonomic profile and functional potential of the gut microbiota.

Trans-ethnic gut microbial signatures of prediabetic subjects from India and Denmark.

BACKGROUND: Recent studies have indicated an association of gut microbiota and microbial metabolites with type 2 diabetes mellitus (T2D). However, large-scale investigation of the gut microbiota of "prediabetic" (PD) subjects has not been reported. Identifying robust gut microbiome signatures of prediabetes and characterizing early prediabetic stages is important for the understanding of disease development and could be crucial in early diagnosis and prevention. METHODS: The current study performed amplification and sequencing on the variable regions (V1-V5) of the 16S rRNA genes to profile and compare gut microbiota of prediabetic individuals (N = 262) with normoglycemic individuals (N = 275) from two cohorts in India and Denmark. Similarly, fasting serum inflammatory biomarkers were profiled from the study participants. RESULTS: After correcting for strong country-specific cohort effect, 16 operational taxonomic units (OTUs) including members from the genera Prevotella9, Phascolarctobacterium, Barnesiella, Flavonifractor, Tyzzerella_4, Bacteroides, Faecalibacterium, and Agathobacter were identified as enriched in normoglycaemic subjects with respect to the subjects with prediabetes using a negative binomial Wald test. We also identified 144 OTUs enriched in the prediabetic subjects, which included members from the genera Megasphaera, Streptococcus, Prevotella9, Alistipes, Mitsuokella, Escherichia/Shigella, Prevotella2, Vibrio, Lactobacillus, Alloprevotella, Rhodococcus, and Klebsiella. Comparative analyses of relative abundance of bacterial taxa revealed that the Streptococcus, Escherichia/Shigella, Prevotella2, Vibrio, and Alloprevotella OTUs exhibited more than fourfold enrichment in the gut microbiota of prediabetic subjects. When considering subjects from the two geographies separately, we were able to identify additional gut microbiome signatures of prediabetes. The study reports a probable association of Megasphaera OTU(s) with impaired glucose tolerance, which is significantly pronounced in Indian subjects. While the overall results confirm a state of proinflammation as early as in prediabetes, the Indian cohort exhibited a characteristic pattern of abundance of inflammatory markers indicating low-grade intestinal inflammation at an overall population level, irrespective of glycemic status. CONCLUSIONS: The results present trans-ethnic gut microbiome and inflammation signatures associated with prediabetes, in Indian and Danish populations. The identified associations may be explored further as potential early indicators for individuals at risk of dysglycemia.

Affective disorders impact prevalence of Flavonifractor and abundance of Christensenellaceae in gut microbiota.

Background Affective disorders (AD) have been associated with a higher prevalence of the gut Flavonifractor genus and a lower abundance of the gut Christensenellaceae family. Objective and methods By pooling two independent study samples of patients with AD (n = 176), their unaffected first-degree relatives (n = 70) and healthy controls (n = 101) we aimed to replicate and extend our prior findings of differential Flavonifractor prevalence and Christensenellaceae abundance when comparing patients with AD and healthy controls. The gut microbiota was profiled using 16S rRNA gene amplicon sequencing. Results The pattern of higher prevalence of Flavonifractor and lower Centered Log-Ratio (CLR) abundance of Christensenellaceae was associated with AD. In generalized linear models the CLR abundance of Christensenellaceae was lower in patients with AD (p = 0.024), and in smokers (p = 1.9*10-4), and inversely associated with increasing waist circumference (p = 0.031). The prevalence of Flavonifractor was higher in patients with AD (p = 0.033) and in smokers (p = 0.036). No impact of psychotropic medication was found. The CLR abundance of Christensenellaceae (p = 0.041), but not the prevalence of Flavonifractor (p = 0.20) could distinguish non-smoking patients with AD from non-smoking healthy controls, whereas no such associations were found in smokers. Unaffected relatives neither differed from patients with AD nor from healthy controls. Conclusion Compared with findings in healthy controls, AD was associated with a significantly lower CLR abundance of the health-linked Christensenellaceae and a significantly higher prevalence of Flavonifractor; findings that are associated with enhanced oxidative stress and systemic low-grade inflammation. If our observations are validated in future independent studies, they support the notion that parts of aberrant gut microbiota are shared by AD and states of dysmetabolism.

Comparative Studies of the Gut Microbiota in the Offspring of Mothers With and Without Gestational Diabetes.

Background: Offspring of mothers with gestational diabetes mellitus (GDM) have increased risk of developing metabolic disorders as they grow up. Microbial colonization of the newborn gut and environmental exposures affecting the configuration of the gut microbiota during infancy have been linked to increased risk of developing disease during childhood and adulthood. In a convenience sample, we examined whether the intestinal tract of children born to mothers with GDM is differentially colonized in early life compared to offspring of mothers with normal gestational glucose regulation. Secondly, we examined whether any such difference persists during infancy, thus potentially conferring increased risk of developing metabolic disease later in life. Methods: Fecal samples were collected from children of mothers with (n = 43) and without GDM (n = 82) during the first week of life and again at an average age of 9 months. The gut microbiota was characterized by 16S rRNA gene amplicon sequencing (V1-V2). Differences in diversity and composition according to maternal GDM status were assessed, addressing potential confounding by mode of delivery, perinatal antibiotics treatment, feeding and infant sex. Results: Children of mothers with GDM were featured by a differential composition of the gut microbiota, both during the first week of life and at 9 months, at higher taxonomic and OTU levels. Sixteen and 15 OTUs were differentially abundant after correction for multiple testing during the first week of life and at 9 months, respectively. Two OTUs remained differentially abundant after adjustment for potential confounders both during the first week of life and at 9 months. Richness (OTU) was decreased in neonates born to mothers with GDM; however, at 9 months no difference in richness was observed. There was no difference in Shannon's diversity or Pielou's evenness at any timepoint. Longitudinally, we detected differential changes in the gut microbiota composition from birth to infancy according to GDM status. Conclusion: Differences in glycaemic regulation in late pregnancy is linked with relatively modest variation in the gut microbiota composition of the offspring during the first week of life and 9 months after birth.

Structured exercise alters the gut microbiota in humans with overweight and obesity-A randomized controlled trial.

OBJECTIVES: Studies suggest that exercise affects the composition and function of the human gut microbiota, yet this has not been investigated in a randomized controlled trial. The primary aim of this study was to assess if exercise alters the diversity, composition and functional potential of the gut microbiota in free-living humans. A secondary aim was to test whether alpha diversity was associated with phenotypical outcomes. METHODS: Eighty eight participants with overweight or obesity completed a 6-month randomized controlled trial with 4 arms; habitual living (CON), active commuting by bike (BIKE) and leisure-time exercise of moderate (MOD) or vigorous intensity (VIG). Faecal samples for 16 s rRNA gene amplicon sequencing were collected prior to randomization and again after 3 and 6 months, with simultaneous registration of phenotypical outcomes and diet. RESULTS: Shannon's diversity index increased by 5% in VIG (CI95 1-9%, P = 0.012) at 3 months compared with CON. No associations were observed between alpha diversity and phenotypical outcomes. Beta diversity changed in all exercise groups compared with CON, particularly the participants in VIG showed decreased heterogeneity. No genera changed significantly. The inferred functional potential of the microbiota in the exercise groups was increased, primarily at 3 months and in MOD. CONCLUSION: Structured exercise induced subtle changes to the human gut microbiota. Cardiorespiratory fitness and fat mass were not associated with alpha diversity.

Motivations for data sharing-views of research participants from four European countries: A DIRECT study.

The purpose of this study was to explore and compare different countries in what motivated research participants' decisions whether to share their de-identified data. We investigated European DIRECT (Diabetes Research on Patient Stratification) research project participants' desire for control over sharing different types of their de-identified data, and with who data could be shared in the future after the project ends. A cross-sectional survey was disseminated among DIRECT project participants. The results found that there was a significant association between country and attitudes towards advancing research, protecting privacy, and beliefs about risks and benefits to sharing data. When given the choice to have control, some participants (<50% overall) indicated that having control over what data is shared and with whom was important; and control over what data types are shared was less important than respondents deciding who data are shared with. Danish respondents indicated higher odds of desire to control data types shared, and Dutch respondents showed higher odds of desire to control who data will be shared with. Overall, what research participants expect in terms of control over data sharing needs to be considered and aligned with sharing for future research and re-use of data. Our findings show that even with de-identified data, respondents prioritise privacy above all else. This study argues to move research participants from passive participation in biomedical research to considering their opinions about data sharing and control of de-identified biomedical data.

Gut microbiota composition in patients with newly diagnosed bipolar disorder and their unaffected first-degree relatives.

OBJECTIVE: An aberrant gut microbiota may be associated with a broad spectrum of diseases including mental illness. The gut microbiota is scarcely studied in bipolar disorder (BD). We examined the gut microbiota composition in patients with newly diagnosed BD, their unaffected first-degree relatives and healthy individuals. METHODS: Stool samples were collected from 113 patients with BD, 39 unaffected first-degree relatives and 77 healthy individuals and the microbiota was profiled using 16S rRNA gene amplicon sequencing. RESULTS: The gut microbiota community membership of patients with BD differed from that of healthy individuals (R2 = 1.0%, P = 0.008), whereas the community membership of unaffected first-degree relatives did not. Flavonifractor was present in 61% of patients with BD, 42% of their unaffected relatives and 39% of healthy individuals. Presence of Flavonifractor was associated with an odds ratio of 2.9 (95%CI: 1.6-5.2, P = 5.8 × 10-4, Q = 0.036) for having BD. When excluding smokers, presence of Flavonifractor was associated with an odds ratio of 2.3 (95%CI: 1.1-5.3, P = 0.019) for having BD. However, when considering the subsample of non-smokers only, BD and presence of Flavonifractor were no longer associated when adjusted for all possible tests at genus level (Q = 0.6). Presence of Flavonifractor in patients with BD was associated with smoking and female sex, but not with age, waist circumference, exercise level, high-sensitive C-reactive protein, current affective state, subtype of BD, illness duration or psychotropic medication, respectively. CONCLUSION: Flavonifractor, a bacterial genus that may induce oxidative stress and inflammation in its host, was associated with BD. Higher prevalence of smoking among patients with BD contributed to our findings, and it cannot be excluded that findings are influenced by residual confounding.

Sharing data for future research-engaging participants' views about data governance beyond the original project: a DIRECT Study.

PURPOSE: Biomedical data governance strategies should ensure that data are collected, stored, and used ethically and lawfully. However, research participants' preferences for how data should be governed is least studied. The Diabetes Research on Patient Stratification (DIRECT) project collected substantial amounts of health and genetic information from patients at risk of, and with type II diabetes. We conducted a survey to understand participants' future data governance preferences. Results will inform the postproject data governance strategy. METHODS: A survey was distributed in Denmark, Sweden, The Netherlands, and the United Kingdom. RESULTS: In total 855 surveys were returned. Ninety-seven percent were supportive of sharing data postproject, and 90% were happy to share data with universities, and 56% with commercial companies. The top three priorities for data sharing were highly secure database, DIRECT researchers to monitor data used by other researchers, and researchers cannot identify participants. Respondents frequently suggested that a postproject Data Access Committee should involve a DIRECT researcher, diabetes clinician, patient representative, and a DIRECT participant. CONCLUSION: Preferences of how data should be governed, and what data could be shared and with whom varied between countries. Researchers are considered as key custodians of participant data. Engaging participants aids in designing governance to support their choices.

Gestational diabetes is associated with change in the gut microbiota composition in third trimester of pregnancy and postpartum.

BACKGROUND: Imbalances of gut microbiota composition are linked to a range of metabolic perturbations. In the present study, we examined the gut microbiota of women with gestational diabetes mellitus (GDM) and normoglycaemic pregnant women in late pregnancy and about 8 months postpartum. METHODS: Gut microbiota profiles of women with GDM (n = 50) and healthy (n = 157) pregnant women in the third trimester and 8 months postpartum were assessed by 16S rRNA gene amplicon sequencing of the V1-V2 region. Insulin and glucose homeostasis were evaluated by a 75 g 2-h oral glucose tolerance test during and after pregnancy. RESULTS: Gut microbiota of women with GDM was aberrant at multiple levels, including phylum and genus levels, compared with normoglycaemic pregnant women. Actinobacteria at phylum level and Collinsella, Rothia and Desulfovibrio at genus level had a higher abundance in the GDM cohort. Difference in abundance of 17 species-level operational taxonomic units (OTUs) during pregnancy was associated with GDM. After adjustment for pre-pregnancy body mass index (BMI), 5 of the 17 OTUs showed differential abundance in the GDM cohort compared with the normoglycaemic pregnant women with enrichment of species annotated to Faecalibacterium and Anaerotruncus and depletion of species annotated to Clostridium (sensu stricto) and to Veillonella. OTUs assigned to Akkermansia were associated with lower insulin sensitivity while Christensenella OTUs were associated with higher fasting plasma glucose concentration. OTU richness and Shannon index decreased from late pregnancy to postpartum regardless of metabolic status. About 8 months after delivery, the microbiota of women with previous GDM was still characterised by an aberrant composition. Thirteen OTUs were differentially abundant in women with previous GDM compared with women with previous normoglycaemic pregnancy. CONCLUSION: GDM diagnosed in the third trimester of pregnancy is associated with a disrupted gut microbiota composition compared with normoglycaemic pregnant women, and 8 months after pregnancy, differences in the gut microbiota signatures are still detectable. The gut microbiota composition of women with GDM, both during and after pregnancy, resembles the aberrant microbiota composition reported in non-pregnant individuals with type 2 diabetes and associated intermediary metabolic traits.