Services. H.Z. has served at scientific advisory boards for Roche Diagnostics, Wave, Samumed and CogRx, has given lectures in symposia sponsored by Biogen and Alzecure, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB, a GU Ventures-based platform company at the University of Gothenburg (outside submitted work). R.A.S. has received personal compensation from AC Immune, Eisai, Roche, and Takeda, and research grant support from Eli Lilly and Janssen. All other authors declare no competing financial interests.

The lack of effective treatments for Alzheimer’s disease (AD) is alarming considering the number of people currently affected by this disorder and the projected increase over the next few decades. Elevated homocysteine levels double the risk of developing AD. Choline, a primary dietary source of methyl groups, converts homocysteine to methionine and reduces age-dependent cognitive decline. Here, we tested the transgenerational benefits of maternal choline supplementation (ChS; 5.0 g/kg choline chloride) in two generations (Gen) of APP/PS1 mice. We first exposed 2.5-month-old mice to the ChS diet and allowed them to breed with each other to generate Gen-1 mice. Gen-1 mice were exposed to the ChS diet only during gestation and lactation; once weaned at postnatal day 21, Gen-1 mice were then kept on the control diet for the remainder of their life. We also bred a subset of Gen-1 mice to each other and obtained Gen-2 mice; these mice were never exposed to ChS. We found that ChS reduced Aβ load and microglia activation, and improved cognitive deficits in old Gen-1 and Gen-2 APP/PS1 mice. Mechanistically, these changes were linked to a reduction in brain homocysteine levels in both generations. Further, RNA-Seq data from APP/PS1 hippocampal tissue revealed that ChS significantly changed the expression of 27 genes. These genes were enriched for inflammation, histone modifications, and neuronal death functional classes. Our results are the first to demonstrate a transgenerational benefit of ChS and suggest that modifying the maternal diet with additional choline reduces AD pathology across multiple generations.

Background Clinical interpretation of genetic variants in the context of the patient’s phenotype is becoming the largest component of cost and time expenditure for genome-based diagnosis of rare genetic diseases. Artificial intelligence (AI) holds promise to greatly simplify and speed genome interpretation by integrating predictive methods with the growing knowledge of genetic disease. Here we assess the diagnostic performance of Fabric GEM, a new, AI-based, clinical decision support tool for expediting genome interpretation. Methods We benchmarked GEM in a retrospective cohort of 119 probands, mostly NICU infants, diagnosed with rare genetic diseases, who received whole-genome or whole-exome sequencing (WGS, WES). We replicated our analyses in a separate cohort of 60 cases collected from five academic medical centers. For comparison, we also analyzed these cases with current state-of-the-art variant prioritization tools. Included in the comparisons were trio, duo, and singleton cases. Variants underpinning diagnoses spanned diverse modes of inheritance and types, including structural variants (SVs). Patient phenotypes were extracted from clinical notes by two means: manually and using an automated clinical natural language processing (CNLP) tool. Finally, 14 previously unsolved cases were reanalyzed. Results GEM ranked over 90% of the causal genes among the top or second candidate and prioritized for review a median of 3 candidate genes per case, using either manually curated or CNLP-derived phenotype descriptions. Ranking of trios and duos was unchanged when analyzed as singletons. In 17 of 20 cases with diagnostic SVs, GEM identified the causal SVs as the top candidate and in 19/20 within the top five, irrespective of whether SV calls were provided or inferred ab initio by GEM using its own internal SV detection algorithm. GEM showed similar performance in absence of parental genotypes. Analysis of 14 previously unsolved cases resulted in a novel finding for one case, candidates ultimately not advanced upon manual review for 3 cases, and no new findings for 10 cases. Conclusions GEM enabled diagnostic interpretation inclusive of all variant types through automated nomination of a very short list of candidate genes and disorders for final review and reporting. In combination with deep phenotyping by CNLP, GEM enables substantial automation of genetic disease diagnosis, potentially decreasing cost and expediting case review.

The colonization of the human gut microbiome begins at birth, and over time, these microbial communities become increasingly complex. Most of what we currently know about the human microbiome, especially in early stages of development, was described using culture-independent sequencing methods that allow us to identify the taxonomic composition of microbial communities using genomic techniques, such as amplicon or shotgun metagenomic sequencing. Each method has distinct tradeoffs, but there has not been a direct comparison of the utility of these methods in stool samples from very young children, which have different features than those of adults. We compared the effects of profiling the human infant gut microbiome with 16S rRNA amplicon vs. shotgun metagenomic sequencing techniques in 338 fecal samples; younger than 15, 15–30, and older than 30 months of age. We demonstrate that observed changes in alpha-diversity and beta-diversity with age occur to similar extents using both profiling methods. We also show that 16S rRNA profiling identified a larger number of genera and we find several genera that are missed or underrepresented by each profiling method. We present the link between alpha diversity and shotgun metagenomic sequencing depth for children of different ages. These findings provide a guide for selecting an appropriate method and sequencing depth for the three studied age groups.

Congenital inner ear malformations affecting both the osseous and membranous labyrinth can have a devastating impact on hearing and language development. With the exception of an enlarged vestibular aqueduct, non-syndromic inner ear malformations are rare, and their underlying molecular biology has thus far remained understudied. To identify molecular factors that might be important in the developing inner ear, we adopted a family-based trio exome sequencing approach in young unrelated subjects with severe inner ear malformations. We identified two previously unreported de novo loss-of-function variants in GREB1L [c.4368G>T;p.(Glu1410fs) and c.982C>T;p.(Arg328*)] in two affected subjects with absent cochleae and eighth cranial nerve malformations. The cochlear aplasia in these affected subjects suggests that a developmental arrest or problem at a very early stage of inner ear development exists, e.g., during the otic pit formation. Craniofacial Greb1l RNA expression peaks in mice during this time frame (E8.5). It also peaks in the developing inner ear during E13-E16, after which it decreases in adulthood. The crucial function of Greb1l in craniofacial development is also evidenced in knockout mice, which develop severe craniofacial abnormalities. In addition, we show that Greb1l zebrafish exhibit a loss of abnormal sensory epithelia innervation. An important role for Greb1l in sensory epithelia innervation development is supported by the eighth cranial nerve deficiencies seen in both affected subjects. In conclusion, we demonstrate that GREB1L is a key player in early inner ear and eighth cranial nerve development. Abnormalities in cochleovestibular anatomy can provide challenges for cochlear implantation. Combining a molecular diagnosis with imaging techniques might aid the development of individually tailored therapeutic interventions in the future.