{"paper_id":"12eb7e56-00db-4050-a052-30fa20a0f391","body_text":"1 \nAlterations of gut microbiota in Down syndrome and their association with \nAlzheimer’s disease \n \nCamilla Pellegrini1, Francesco Ravaioli1,#, Sara De Fanti 1, Claudia Sala2, Magali Rochat1, Virginia \nPollarini1, Polischi Barbara 1, Alberto Pasti 1, Margherita Grasso 3, Maria Rambaldi 4, Francesco \nCardoni1, Nicola Grotteschi1,4, Filippo Caraci3,5, Pietro Cortelli4, Federica Provini1,4, Raffaele Lodi1,4, \nLuca Morandi1,4, Piero Parchi 1,4, Gian Luca Pirazzoli 1, Luisa Sambati 1, Caterina Tonon 1,4,§, Maria \nGiulia Bacalini1,4,§ \n  \n1IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy \n2Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy \n3Oasi Research Institute - IRCCS, Troina, Italy \n4Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, \nItaly \n5 Department of Drug and Health Sciences, University of Catania, Catania, Italy \n \n# Corresponding author:  \nFrancesco Ravaioli, IRCCS Istituto delle Scienze Neurologiche di Bologna, via Altura 3, 40139, \nBologna, Italy \nEmail: francesco.ravaioli@ausl.bologna.it \n \n§ shared senior authorship \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \nAbbreviations: CTRL, Control euploid subjects; DS, Down syndrome; AD, \nAlzheimer’s disease; NcD, Major Neurocognitive Disorder; CNS, Central \nNervous System; GM, Gut microbiota \n \n2 \n \nStructured Abstract \nINTRODUCTION:  \nAdults with Down syndrome (DS) have a higher risk of developing Alzheimer’s disease (AD). As \ngut microbiota (GM) alterations have been reported in AD, we investigated their association with \ncognitive decline and plasma AD biomarkers in DS. \nMETHODS:  \nFecal and plasma samples were collected from 58 adults with DS (21-75 years) and 30 euploid \ncontrols (CTRL; 25-83 years). GM was profiled using 16S rRNA sequencing. Major Neurocognitive \nDisorder (NcD) was diagnosed according to DSM -5 criteria. Plasma levels of p -Tau181, NfL, and \nGFAP were measured using the Simoa platform. \nRESULTS:  \nCompared with CTRL, DS showed significant changes in UBA1819 and Intestinibacter genera, \npreviously reported to be associated with mild cognitive impairment. Furthermore, DS with NcD \nwere characterized by a reduced abundance of Roseburia genus, which was also negatively associated \nwith plasma levels of AD biomarkers. \nCONCLUSION:  \nAdults with DS display AD-associated changes in GM partially resembling those previously reported \nin euploid AD patients \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \nAbbreviations: CTRL, Control euploid subjects; DS, Down syndrome; AD, \nAlzheimer’s disease; NcD, Major Neurocognitive Disorder; CNS, Central \nNervous System; GM, Gut microbiota; BBB, Blood –brain barrier; LPS, \nLipopolysaccharides; SCFAs, Short-chain fatty acid; MCI, Mild Cognitive \nImpairment \n \n3 \n \n1. Background \nDown syndrome (DS) is a genetic disorder caused by complete or partial triplication of chromosome \n21. DS occurs in approximately 1 –2 per 1000 live births globally, with a worldwide prevalence of \n1/800 [1]. Individuals with DS present an increased risk for various health issues, including congenital \nheart disease, developmental delay, leukemia, obesity, obstructive sleep apnea, and abnormalities in \nmyelopoiesis and inflammatory responses [2–4]. Alterations in brain development lead to a reduction \nin total brain volume, particularly in the cortical, hippocampal, and cerebellar regions, and are \nassociated with intellectual disability of variable severity [5].  Furthermore, the overexpression of the \nβ-amyloid precursor protein (APP) gene, located on chromosome 21, increases the risk of developing \nAlzheimer’s disease (AD)–related dementia in adults with DS [6]. By age 40, pathological features \nof AD are already detectable in cerebrospinal fluid (CSF) and plasma, as demonstrated by several \nstudies reporting elevated levels of neurofilament light protein (NfL), phosphorylated Tau (pTau181, \npTau217), glial fibrillary acidic protein (GFAP), and a decline in the ratio of proteins Aβ -42/Aβ-40 \n[7–10]. However, the age of onset and progression of dementia in DS are highly variable, suggesting \nthe existence of factors that can modulate the AD pathological cascade, as observed in the general \npopulation.  \nThe gut microbiota (GM) represents the most densely populated bacterial community in the human \nbody and plays an essential role in maintaining overall health. Intestinal bacteria and their metabolites \nsupport key functions including preserving gut barrier integrity, modulating the immune system, and \nregulating essential metabolic processes [11]. Moreover, the gut microbiome can influence brain \nfunction and homeostasis through the bidirectional communication network known as the gut -brain \naxis. This axis transmits information via neural, immune, and endocrine pathways, thereby impacting \nmood, cognitive functions, including memory, cognition and social behavior, and its alterations can \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n \n \n4 \ncontribute to the onset and progression of neurological and psychiatric disorders [12–16]. Several \nstudies have suggested a link between GM alterations, AD and its preclinical conditions, reporting \nchanges in microbial composition along the AD continuum [17–20]. Altered taxa composition may \ncontribute to AD pathogenesis through several mechanistic pathways. Dysbiosis has been linked to \nelevated production of lipopolysaccharides (LPS) and microbial amyloids, which can compromise \nintestinal epithelial integrity an d disrupt the blood –brain barrier (BBB). These alterations facilitate \nsystemic and neuroinflammatory responses, promote oxidative stress, sustain amyloid -beta (Aβ) \naggregation, induce central insulin resistance, and ultimately lead to neuronal apoptosis, all of which \nare characteristic features of AD neuropathology [21–23]. \nStudies investigating the GM in individuals with DS are limited, but available results suggest an \nimbalance in both microbial composition and metabolite profile compared to euploid subjects. These \ndifferences were evident even during childhood and have bee n associated with cognitive and \nbehavioral disturbances [24–26]. Interestingly, a recent metagenomic study investigated fecal \nmicrobiota in a cohort of 20 DS cognitively stable or with mild cognitive impairment (MCI) and \nreported both overall and taxa-specific changes according to cognitive status [27]. \nThe present study seeks to advance understanding of the role of GM in individuals with DS, with \nparticular focus on its association with the development of AD. We investigated the fecal microbiota \nof adults with DS using 16S rRNA high -throughput sequencing and analysed its association with \nplasma levels of AD-related biomarkers [28,29], including phosphorylated pTau181, NfL, and GFAP. \n  \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n \n \n5 \n2. Methods \n2.1 Cohort \nParticipants with DS and healthy controls were recruited at AUSL Bologna - IRCCS Istituto delle \nScienze Neurologiche of Bologna (Italy) in the framework of the study protocols “Study of aging in \npeople with Trisomy 21: longitudinal evaluation of molecular markers and clinical -functional, \nneuropsychological and cognitive aspects (AgingInT21)” and “Digital biomarkers in P arkinson and \nAlzheimer diseases and in subjects with Down Syndrome (DARE -T21)”. The protocols were \napproved by the Local Ethics Committee of the local health service of Bologna, Italy (1070 -2021-\nSUPER-AUSLBO and 378-2024-OSS-AULSBO) and informed written co nsent was obtained from \nthe participants and from their relatives or legally authorized representatives. Geriatric and \nneurological evaluation was performed by expert clinicians according to a standardized protocol, as \npreviously described [30]. Major Neurocognitive Disorder (NcD) was diagnosed according to DSM-\n5 TR criteria [31]. \n \n2.2 Sample collection and DNA extraction  \nFecal samples were collected in  OMNIgene®•GUT tubes to stabilize microbial DNA (DNA \nGenotek, Canada). Samples were stored for a maximum of 7 days at room temperature, vortexed 60 \nsec, transferred to cryotubes and stored at -80°C. Microbial DNA was extracted from faeces using a \nmodified version of the protocol described by Ghosh et al  [32].  Briefly, 200 ul of defrosted faeces \nwere lysed using the ASL buffer (QIAGEN, Hilden, Germany) and bead beaten 2 times at 1800 rpm \nfor 3 min, with a 1-minute pause between the 2 cycles, in Power Bead Tubes (Ceramic 1.4 mm) using \nthe PowerLyzer 24 Homogenizer (QIAGEN, Hilden, Germany).  After proteinase K treatment, DNA \npurification was performed using the QIAamp Fast DNA Stool Mini Kit (QIAGEN, Hilden, \nGermany). DNA was quantified using Qubit ™ dsDNA Broad Range (BR) Assay Kit (Qiagen, \nHilden, Germany) and stored at -20°C before analysis. \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n \n \n6 \n2.3 Analysis of plasma AD biomarkers \nVenous blood was collected at fasting using sodium ethylenediaminetetraacetic acid (EDTA) tubes. \nBlood samples were centrifuged at 2000×g at room temperature for 10  min within 2  hours from \ncollection. Plasma supernatant was collected, divided into aliquots , and frozen at−80  °C until use. \nPlasma p-Tau181, NfL and GFAP were measured with SiMOA p-tau181 advantage V2 and SiMOA \nNeurology 2-Plex B (GFAP, NF -l) Assay Kit, respectively. Analyses were performed on a SiMOA \nSR-X analyzer platform (Quanterix, Billerica, MA, USA). Biomarker levels were transformed using \na base-2 logarithm. \n \n2.4 Library Construction and Sequencing  \nLibrary preparation was conducted following Illumina 16S Library Preparation Workflow. \nSpecifically, the 16S rRNA gene hypervariable V3-V4 region was amplified with primers 341F and \n805R. The PCR products were purified using MagSi Prep Plus magnetic beads (Magtivio, NL) and \namplified for 8 cycles using Nextera XT Indexed Primers.  The final amplicons were purified, \nquantified using Qubit ™ dsDNA BR Assay Kit (Qiagen, Hilden, Germany) and normalized at \nequimolar concentration (4nM). Pooled libraries were denatured with 0.2 N NaOH, diluted and \ncombined with 10% PhiX Sequencing control V3. The final pool (6 pM) was sequenced with MiSeq \nv3 reagents (Illumina, San Diego, CA) on Illumina MiSeq platform using paired -end 2 x 300‐bp \nreads.  \n \n2.5 Bioinformatic processing  \nPre-processing of raw paired-end reads was performed according to Dada2 Big Data pipeline [33] in \nR (v. 4.2.2). Briefly, forward and reverse reads were checked for quality and trimmed to remove \nIllumina adapters and low-quality sequences. Filtered reads were deduplicated, merged and clustered \ninto an amplicon sequence variant (ASV) table. Finally, after removal of chimeric ASVs, taxonomy \nwas assigned against SILVA non -redundant small subunit ribosomal RNA database (v138.1) [34], \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n \n \n7 \nwith default bootstrap confidence value (50%). Samples with low sequencing depth (<10000 reads) \nwere excluded from the analysis (88 samples remaining). Taxa that were assigned to neither Bacteria \nnor Archaea and taxa present in less than 10% of the total sample size were removed from the ASVs \ncount table. \n \n2.6 Statistical analyses  \nAll statistical analyses were performed with R (v. 4.2.2). Age and sex were included in all parametric \nstatistical models as confounding variables. For analyses performed within the DS group, Body Mass \nIndex (BMI) was included as a covariate (correction wa s not applied to euploid controls due to \nunavailability of BMI data). Statistically significant threshold was considered at nominal p -\nvalues<0.05; in addition, false discovery rate (FDR) according to the Benjamini -Hochberg (BH) \nmethod was calculated Alpha and beta diversity at ASVs level were calculated using the phyloseq \npackage (v 1.42.0) [35]. Alpha diversity was calculated according to the number of observed species, \nChao, Shannon and inverted Simpsons indexes. Wilcoxon rank -sum test was used to compare alpha \ndiversity measurements between DS and CTRL groups, as alpha diversity data was not n ormal \naccording to the Shapiro -Wilk test. The association between alpha diversity metrics and levels of \nplasma markers p-Tau181, NfL and GFAP in DS subjects was evaluated by fitting a linear regression \nmodel. Beta diversity was assessed via Principal Component Analysis (PCoA) based on Bray-Curtis \ndissimilarity, weighted and unweighted Unifrac metrics. PERMANOVA function in vegan R package \n(v 2.6 -6.1) was used to compare beta -diversity metrics between DS and CTRL participants. \nAlterations in microbial abundances were evaluated at phylum, family and genus level. Firstly, \ndysbiosis was evaluated by calculating Firmicutes/Bacteroidetes ratio and compared between DS and \nCTRL participants using ANOVA test. Secondly, DESeq2 pipeline [36] using Wald test was used to \nperform differential microbial abundance analyses between DS and CTRL, as well as between DS \nwith and without NcD. An alternative analysis of differential abundance was performed using the \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n \n \n8 \nAldex2 method [37]. The association between microbial abundance and AD plasma biomarkers was \nalso assessed using the DESeq2 pipeline. Finally, predictive functional profiling was performed using \nPICRUSt2 (v. 2.6.2) [38] . Predicted abundances were normalized with Centered Log -Ratio (CLR) \ntransformation using the compositions package (v. 2.0 -6). Differential pathway abundance analysis \nin DS versus CTR and in DS with NcD versus DS without, as well as the association of pat hway \nabundance with AD biomarkers, were conducted in R using limma package (v. 3.54.2). \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n \n \n9 \n3. Results \n3.1 Demographic characteristics of participants  \nAfter quality filtering, metagenomic data were available for 58 adults with Down Syndrome (DS; 20 \nfemales, mean age 42 years) and 30 euploid controls (CTRL; 24 females, mean age 58 years). Nine \nDS participants had a diagnosis of Major Neurocognitive Disord er (NcD), while 5 had chronic \ngastrointestinal diseases. Mean value of Body Mass Index (BMI) in DS was 27.7 (13 with BMI>30, \nobese). BMI values were not available for CTRLs.  Demographic and clinical characteristics of the \ncohort are summarized in Table 1. \n \n3.2 Plasma AD biomarkers  \nabundance with AD biomarkers, were conducted in R using limma package (v. 3.54.2). \nPlasma levels of AD biomarkers (pTau181, NfL  and GFAP) were available for 51 DS (19 females; \nmean age 40 years; 9 with a diagnosis of NcD) and 12 CTRL (8 females; mean age 40 years).  As \nexpected [29], biomarker levels were higher in DS compared to CTRL (ANOVA correcting for age \nand sex; pTau181: p -value=0.018; NfL: p -value<0.001; GFAP: p -value=0.001; Figure 1A ) and \nshowed a relevant increase after 40 years in the DS group (Figure 1B). Furthermore, pTau181 and \nNfL were significantly higher in DS with NcD than in DS without NcD (ANOVA correcting for age \nand sex; pTau181: p-value=0.025; NfL: p-value=0.017; Figure 1C). \n \n3.3 Analysis of gut microbiota in DS and CTRL groups \nThe 16S rRNA amplicon sequencing yielded a total of 2284703 reads (ranging from 11177 to 57267 \nper sample) passing quality filters. After prevalence filtering, the dataset comprised 275 ASVs that \nwere assigned to 6 phyla, 21 families and 62 genera. \nAs a first step, we evaluated differences between CTRL and DS groups in terms of overall microbiota \ndiversity (alpha and beta-diversity) and microbial abundance at phylum, family and genus levels.  \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n \n \n10 \nAlpha diversity, which is a within-sample measure of microbiota diversity, did not show significant \ndifferences between DS and CTRL groups (Wilcoxon test p -value>0.05; Figure 2A  and \nSupplementary File 1 ). The analysis of beta diversity, which measures microbial community \ndissimilarities among groups, showed significant differences between DS and CTRL groups with \nBray-Curtis distance (p -value=0.021), but not with Weighted and Unweighted Unifrac metrics \n(Figure 2B and Supplementary File 1).  \nWe used DESeq2 to analyze differential microbial abundance in DS compared to CTRL participants \nat different taxonomic levels (phylum, family and genus) (Supplementary File 1). \nThe analysis of bacterial phyla abundance revealed no statistically significant differences between \ngroups. Furthermore, the ratio of Firmicutes to Bacteroidetes (F/B ratio) was not altered in DS \ncompared to CTRL (Figure 2C and Supplementary File 1). At the family level, we found that the \nabundance of Tennerellaceae and Clostridiaceae was significantly higher in DS than in CTRL \n(nominal p-value: 0.012, 0.012, respectively; Figure 2C and Supplementary File 1 ). Finally, we \nidentified 8 genera that showed significant abundance alterations in DS compared to CTRL Figure \n2C and Supplementary File 1): UCG-003 (nominal p-value= 0.039) and Lachnospiraceae NK4A136 \ngroup (nominal p-value= 0.002) were reduced in DS, while Lachnoclostridium (nominal p-value= \n0.044), Oscillibacter (nominal p -value= 0.021) , Intestinibacter (nominal p -value= 0.020) , \nParabacteroides (nominal p-value= 0.025), Clostridium sensu stricto 1 (nominal p-value= 0.004) and \nUBA1819 (nominal p -value<0.001) genera  were increased in DS . For UBA1819 statistical \nsignificance survived also after false discovery rate (FDR) correction (q -value=0.028) (Figure 2C \nand Supplementary File 1).  \nTo confirm the above-described results, we used an alternative analytical approach based on Aldex2 \npackage. This analysis confirmed the alterations between DS and CTRL for Parabacteroides, \nIntestinibacter and Lachnospiraceae NK4A136 group genera (nominal p -value= 0,029; 0,020 and \n0,043, respectively). Moreover Lachnospiraceae UCG -010, Clostridium sensu stricto 1 and  \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n \n \n11 \nUBA1819 were marginally significant (nominal p -value= 0,056; 0,059 and 0,059, respectively) \n(Supplementary File 2). \nFinally, functional abundance analysis performed using PICRUSt2 tool identified 32 significant \npathways in the comparison between DS and CTRL groups ( Supplementary File 3 ). Considering \nthe higher-level category annotations, we found that DS showed a reduction in several significant \npathways related to quinol and quinone biosynthesis (12/32), including menadione (vitamin K2) \nbiosynthesis.  \n3.4 Gut microbiota analysis according to clinical diagnosis of Major Neurocognitive Disorder \nTo evaluate a possible association between GM composition and cognitive status in adults with DS, \nwe compared DS subjects with and without a clinical diagnosis of NcD. \nAnalysis of alpha diversity did not reveal significant differences for any index, while beta diversity \ncalculated with Unweighted UniFrac index differed between DS with and without NcD ( Figure 3A \nand B and Supplementary File 4 ). In the analysis of taxa abundance, the Firmicutes phylum \nabundance was significantly reduced in DS with NcD (nominal p-value= 0.048), while no significant \ndifferences emerged in the F/B ratio (data not shown). At the family level, DS with NcD showed a \nreduction of Peptostreptococcaceae (nominal p -value= 0.023) and an increase of Tannerellaceae \n(nominal p-value=0.027) (Figure 3C and Supplementary File 4 ). At genus level, DS with NcD \nshowed a decrease of Roseburia (nominal p-value=0.004) and Lachnospiraceae UCG-010 (nominal \np-value=0.005), and an increase of Parabateroides (nominal p value=0.017), Alistipes (nominal p-\nvalue=0.037) and Butyricicoccus (nominal p value=0.039) (Figure 3C and Supplementary File 4). \nFunctional abundance analysis identified 2 significant pathways (Biosynthesis of Quinol and \nQuinone, and Fatty Acids and Lipid Biosynthesis classes), which were increased in DS with NcD \n(Supplementary File 3). \n \n \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n \n \n12 \n3.5 Gut microbiota analysis according to plasma AD biomarkers  \nFinally, we analyzed the association between GM composition and plasma AD biomarkers in DS \nparticipants. No significant associations were found between alpha diversity metrics and plasma \nlevels of p -Tau181, NfL or GFAP. Conversely, we detected significant associations for specific \ngenera (Figure 4A and Supplementary File 5). In particular, we found a significant association with \np-Tau181 for the 3 genera Roseburia (nominal p -value= 0.033) , Lachnospira (nominal p -value= \n0.020) and UBA1819 (nominal p-value= 0.009); a significant association with NfL for the 2 genera \nRoseburia (nominal p-value= 0.035) and Christensenellaceae R-7 group (nominal p-value= 0.013); \nand a significant association with GFAP for the 2 genera [Eubacterium] siraeum group (nominal p-\nvalue= 0.005) and Lachnospiraceae UCG -001 (p-value= 0.014). Notably, Roseburia showed a \nsignificant negative association with both p-Tau181 and NfL, and it showed a marginally significant \nassociation with GFAP (nominal p-value= 0.055) (Figure 4B and Supplementary File 5). \nFunctional abundance analysis identified no pathway significantly associated with p -Tau181, \nwhereas 55 and 11 pathways emerged as significantly associated with NfL and GFAP, respectively \n(Supplementary File 3). In particular, we found several pathways annotated within the Proteinogenic \nAmino Acid Biosynthesis (4/55), Enzyme Cofactor Biosynthesis (8/55) and Alcohol Degradation \n(4/55) classes that were negatively associated with NfL. In addition, we identified several pathways \nannotated within the Fatty Acids and Lipid Biosynthesis (4/55) classes that were positively associated \nwith NfL. Notably, several pathways related to Fermentation to Short -Chain Fatty Acids class that  \nwere significantly reduced in the DS group were also negatively associated with NfL and GFAP \nplasma levels (Supplementary File 3). \n \n4. Discussion  \nIn this study, we analyzed the gut microbiome composition in adults with DS in comparison with \neuploid controls, and we further examined how microbiome variation relates to clinical diagnosis of \nNcD and to the levels of plasma AD biomarkers.   \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n \n \n13 \nOur data suggest no major differences in the overall gut microbiota composition of adults with DS \ncompared to euploid subjects, in accordance with what was previously reported by Biagi et al. in a \ncohort having demographic characteristics similar to ours [24]. In particular, we found that the DS \ngroup exhibited weak but significant differences in beta -diversity based on Bray –Curtis metric, \nwhereas no variations in alpha -diversity metrics were observed. Conversely, differences in alpha \ndiversity with respect to euploid controls were previously reported in children and young adults with \nDS [25,26], although with a discordant direction of change in the two available studies. These \nheterogeneous results can be ascribed to differences in the demographic characteristics of the cohorts \nevaluated in our and previous studies, limited sample sizes, and var iations in experimental and \nanalytical pipelines. Similarly, there is no overlap in the results of differential abundance analysis \nbetween DS and CTRL groups across the different studies, including ours. Despite the similarities in \nthe demographic characteristics of the cohorts, a direct comparison with Biagi et al. is not possible, \nas our analytical pipeline filtered out the low prevalence genera reported there as significant \n(Parasporobacterium, Sutterella and Veillonellaceae) [24]. Functional abundance analysis in our \ndataset identified a reduction of pathways related to menaquinone (Vitamin K2) biosynthesis in DS. \nMenaquinone, mainly produced by the GM, is known to improve bone health and prevent coronary \ncalcification, but several studies have also reported a key role in preserving cognitive functions [39] \nand brain health [40]. Animal studies showed that menaquinone administration can reverse cognitive \nchanges induced by antibiotic-induced gut dysbiosis, pointing to a neuroprotective role mediated by \na reduction of oxidative stress and inflammation in intestine and brain [41]. Therefore, we can \nhypothesize that the GM changes that we observed in our dataset may contribute to the enhanced \nneuroinflammation characteristic of DS [42]. \nAs adults with DS are genetically at higher risk of developing AD at an early age, it is of interest to \ninvestigate whether the GM alterations described in euploid AD patients are already present in our \nentire DS cohort, which includes participants of different ages and with and without cognitive decline. \nAmong the genera identified by differential abundance analysis, Clostridium sensu stricto 1  and \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n \n \n14 \nIntestinibacter were previously reported to be decreased in AD patients [43,44], while they showed \nthe opposite direction of change in our DS cohort. Conversely, UBA1819 and Intestinibacter were \nreported to be elevated in euploid subjects with a clinical diagnosis of MCI in a Greek cohort [45], \nconsistent with our findings. These results suggest that, when considering our entire cohort, the \nobserved GM alterations show some similarities with those reported in MCI, but not with those \ndescribed in AD patients. Within this framework, it is worth n oting that some studies suggest the \npresence of stage -specific GM changes along the AD continuum in the general population, with \nalterations observed in AD being only partially detected in patients with clinical MCI and vice-versa \n[46,47]. \nWe then specifically evaluated the GM alterations associated with Major Neurocognitive Disorder in \nDS. To the best of our knowledge, only Rosas et al. recently investigated this topic, comparing 14 \ncognitively stable DS and 6 DS with MCI, designed on the basis of the assessment of subtle cognitive \nand/or functional decline [27]. Our dataset included a clinical characterization (diagnosis of major \nNcD by DSM -5 criteria) and a biological characterization (plasma biomarkers) of AD associated \ncognitive decline.  \nWhen comparing participants with DS with and without NcD, we found a slight but significant \ndifference in beta diversity and a reduction of Firmicutes phylum in the NcD group, in accordance \nwith the results reported by Rosas et al. [27]. Firmicutes phylum includes many SCFAs producers \nwith protective and anti -inflammatory properties [48], and its reduction has been reported in AD \n[20,49]. Our differential abundance analysis revealed additional taxa previously reported to be altered \nin euploid AD patients. Among them, there are the Peptostreptococcaceae family, reduced in the \nNcD DS group as in AD [50], and the Alistipes and Roseburia genera, respectively increased and \ndecreased in the NcD group, which have been consistently reported as altered also in AD and \nassociated with cognitive decline [18,51–53]. \nThe analysis of the association between taxa abundance and plasma AD biomarkers in participants \nwith DS further expanded the results described above. Remarkably, we found that the abundance of \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n \n \n15 \nRoseburia genus showed a negative association with all the biomarkers, confirming similar analyses \nperformed on CSF AD biomarkers (amyloid-β1-42 and p-tau) in euploid patients [18]. The latter study \nalso identified Christensenellaceae R7 group genus, which was negatively associated with NfL in our \ndataset and was also reported to be reduced in DS with MCI by Rosas et al [54]. In addition, UBA1819 \ngenus, which we found significantly increased in DS compared to euploid controls, was positively \nassociated with p-Tau181. \nIn summary, our results extend previous findings on GM alterations and cognitive decline in DS and \nhighlight for the first time their association with plasma AD biomarkers. These results require further \nvalidation in larger cohort studies and should be com plemented by additional characterizations, \nincluding fecal metabolomic profiling, to better elucidate the functional implications of the microbial \nchanges that we observed in the pathogenesis and progression of AD in adults with DS. This line of \ninvestigation holds substantial promise for future research and may identify novel targets for early \nintervention against AD in adults with DS. \n \n \nReferences (max 75) \n[1] Chen L, Wang L, Wang Y, Hu H, Zhan Y, Zeng Z, et al. Global, Regional, and National Burden \nand Trends of Down Syndrome From 1990 to 2019. Front Genet 2022;13:908482. \nhttps://doi.org/10.3389/fgene.2022.908482.  \n[2] Antonarakis SE, Skotko BG, Rafii MS, Strydom A, Pape SE, Bianchi DW, et al. Down \nsyndrome. Nat Rev Dis Primers 2020;6:9. https://doi.org/10.1038/s41572-019-0143-7.  \n[3] Lagan N, Huggard D, Mc Grane F, Leahy TR, Franklin O, Roche E, et al. 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It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n \n \n23 \nAcknowledgements \nThe authors thank all the people with Down syndrome who participated in the study and their families. \nThe authors thank Marica Lanzoni, Claudia Boninsegna, Elisabetta Venieri and Silvia De Luca  \n(IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologn a, Italy) for their assistance in \nplanning and organizing the study operational procedures. \n \nConflict of Interest \nCP, FR, SDF, CS, MR, VP, PB, AP, MG, MR, FC, NG, FC, PC, FP, RL, LM, PP, GLP, LS, CT, \nMGB reported no conflicts of interest. \n \nSource of Funding \nThe publication of this article was supported by: the Italian Complementary National Plan PNC -1.1 \n“Research initiatives for innovative technologies and pathways in the health and welfare sector” D.D. \n931 of 06/06/2022, “DARE —DigitAl lifelong pRvEntion” initiative, code PNC0000002, CUP: \nB53C22006450001; the Italian Ministry of Health, grant no: GR-2019-12369983-Theory-enhancing; \nthe “Ricerca Corrente” funding from the Italian Ministry of Health. \n \nConsent Statement \nAll participants gave their written informed consent for the use of their biological material and clinical \ndata for research purposes. Ethical approval was granted by the Local Ethics Committee of the local \nhealth service of Bologna. \n \nKeywords \nMetagenomics, Down syndrome, Alzheimer’s disease, plasma biomarkers, gut microbiota, major \nneurocognitive disorder. \n  \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n CTRL group (n= 30)  DS group (n= 58) p \nDemographic    \nAge (mean years, range) 58 (25-83) 42 (21-75) <0.001* \nFemales (n/total) 24/30 20/58  <0.001† \nBMI (mean ±SD) / 27.7±5.9 / \nDementia clinical diagnosis     \nMajor Neurocognitive Disorder (n) / 9  / \nComorbidities (n)    \nGastrointestinal disorders / 5 / \nType 2 Diabetes / 0 / \n \nTable 1. Demographic characteristics of participants \nAbbreviations: SD, corresponds to standard deviation; n, number; DS, Down Syndrome participants; CTRL, \neuploid subjects; p, p-value.  \n*, calculated by t-test; †, calculated by Fisher test. \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\npTau181\nAge\nDS wNcd\nDS wNcd\nDS wNcd\nDS w/oNcD\nDS w/oNcD\nDS w/oNcD\nAge\nAge\nCTRL\nCTRL\nCTRL\nDS\nDS\nDS\nNfLGFAP\npTau181NfLGFAP\npTau181NfLGFAP\nA B C\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\nCTRL\nCTRL\nDS\nDS\nShannon Diversity index\nPC1\nPC2\nBray Curtis distance\nWilcoxon p-value=0.685\nPERMANOVA p-value=0.021\nIncreased in DS\nReduced in DS\nLegend\na: Parabacteroides genus\nb: Clostridium sensu stricto 1 genus\nc: Lachnoclostridium genus\nd: Lachnospiraceae NK4A136 group genus\ne: Oscillibacter\nf: UCG-003 genus\ng: UBA1819 genus\nh: Intestinibacter genus\ni: Tannerellaceae family\nj: Clostridiaceae family\nA B \nC \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\nDSw/oNcD\nShannon Diversity index\nWilcoxon p-value=0.318\nUnweighted UniFrac distance\nPERMANOVA p-value=0.047\nDS w/oNcD DS wNcD\nPC1\nPC2\nDSwNcD\nReduced in DSwNcD\nIncreased in DSwNcD Legend\na: Alistipes genus\nb: Parabacteroides\nc: Lachnospiraceae UCG-010 genus\nd: Roseburia genus\ne: Butyricicoccus genus\nf: Tannerellaceae family\ng: Peptostreptococcaceae family\nh: Firmicutes phylum\nA B \nC \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\np-Tau181\np-Tau181\nGFAPNfL\nAbundance\nAbundance\nAbundance\nRoseburia\np-value=0.033\nRoseburia\np-value=0.055\nRoseburia\np-value=0.035\nB\nA\nNfL\nGFAP\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n \n \n24 \nFigure 1. Plasma levels of p-Tau181, NfL and GFAP \nA. Boxplots of pTau181, NfL and GFAP levels in DS (red) and CTRL (blue) groups. Sample size n=63. B. \nScatterplots of pTau181, NfL and GFAP levels with respect to the age of DS (red) and CTRL (blue); DS with \nNcD are colored in dark red. Sample size n=63. C. Boxplots of pTau181, NfL and GFAP levels in DS without \nNcD (w/oNcD, yellow) and DS with NcD (wNcD, dark red). Plasma biomarker levels are reported as z-scores \nof base-2 logarithm-transformed values. Sample size n=51. \n \nFigure 2. Microbial diversity and taxa abundance differences between the DS and CTRL groups \nA. Boxplot showing alpha-diversity values calculated according to Shannon index in DS and CTRL groups. \nGroup means are indicated with a blue X symbol; group medians are indicated with a continuous black line. \nSample size n=88. B. Beta diversity plot showing separation of DS (red) and CTRL (blue) groups based on \nBray-Curtis dissimilarity metric. Sample size n=88. C. Cladogram showing different abundant taxa levels in \nthe DS group as identified by Deseq2 analysis. Microbial families showing significant changes are highlighted \nin yellow, while genera are highlighted in orange. Blue and red dots indicate taxa significa ntly reduced and \nincreased in the DS group, respectively. The dimension of each dot is proportional to the Log2 Fold Change \n(Log2FC). Sample size n=88. \n \nFigure 3. Microbial diversity and taxa abundance differences between DS with and without NcD. \nA. Boxplot showing alpha-diversity values calculated according to Shannon index in DS wNcD  and w/oNcD \ngroups. Group means are indicated with a blue X symbol; group medians are indicated with a continuous black \nline. Sample size n=58. B. Beta diversity PCoA plot showing separation of DS wNcD (dark red)  and DS \nw/oNcD (yellow) groups based on unweighted UniFrac metric. Sample size n=58. C. Cladogram showing the \ndifferentially abundant taxa levels between DS wNcD and w/oNcD groups as identified by DeSeq2 analy sis. \nMicrobial phyla showing significant changes are highlighted in green, families in yellow, while genera are \nhighlighted in orange. Taxa significantly increased in the DS wNcD group are indicated with dark red dots, \nwhile those reduced in DS wNcD in yellow. The dimension of each dot is proportional to the Log2 Fold Change \n(Log2FC). Sample size n=58. \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint \n\n \n \n \n25 \nFigure 4. Association analysis of genera abundance and AD plasma biomarkers. \nA. Correlation matrix between plasma AD biomarkers (p -Tau181, NfL and GFAP) and genera abundance in \nDS participants. The matrix reports only the genera that show a significant association with at least one \nbiomarker. Colors indicate Pearson correlation coefficient values. The elliptical shape indicates the strength of \ncorrelation between microbial genus and plasma biomarker. In the correlation visualization, bolder colors \nindicate higher correlations. If the shape of an ellipse bends towards the right, it indicates positive correlation, \nwhereas negative correlation if its shape bending towards the left shows a negative correlation. Sample size \nn=47. B. Scatterplots reporting an example of the results obtained from the association with AD plasma \nbiomarkers levels. Roseburia abundance is represented in association with p-Tau181, NfL and GFAP plasma \nlevels. Sample size n=46. \n \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.03.716276doi: bioRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}