Shared and distinct biological mechanisms for anxiety and sensory over-responsivity in youth with autism versus anxiety disorders.

Sensory over-responsivity (SOR) is a prevalent cross-diagnostic condition that is often associated with anxiety. The biological mechanisms underlying the co-occurrence of SOR and anxiety symptoms are not well understood, despite having important implications for targeted intervention. We therefore investigated the unique associations of SOR and anxiety symptoms with physiological and neural responses to sensory stimulation for youth with anxiety disorders (ANX), autism spectrum disorder (ASD), or typical development (TD). Age/IQ-matched youth aged 8-18 years (22 ANX; 30 ASD; 22 TD) experienced mildly aversive tactile and auditory stimuli during functional magnetic resonance imaging and then during skin conductance response (SCR) and heart rate (HR) measurements. Caregivers reported on participants' SOR and anxiety symptoms. ASD/ANX youth had elevated SOR and anxiety symptoms compared to TD. ASD/ANX youth showed similar, heightened brain responses to sensory stimulation compared to TD youth, but brain responses were more highly related to SOR symptoms in ASD youth and to anxiety symptoms in ANX youth. Across ASD/ANX youth, anxiety symptoms uniquely related to greater SCR whereas SOR uniquely related to greater HR responses to sensory stimulation. Behavioral and neurobiological over-responsivity to sensory stimulation was shared across diagnostic groups. However, findings support SOR and anxiety as distinct symptoms with unique biological mechanisms, and with different relationships to neural over-reactivity dependent on diagnostic group. Results indicate a need for targeted treatment approaches.

Major stress in early childhood strengthens the association between peripheral inflammatory activity and corticostriatal responsivity to reward.

BACKGROUND: Severe, chronic stress during childhood accentuates vulnerability to mental and physical health problems across the lifespan. To explain this phenomenon, the neuroimmune network hypothesis proposes that childhood stressors amplify signaling between peripheral inflammatory cells and developing brain circuits that support processing of rewards and threats. Here, we conducted a preliminary test of the basic premises of this hypothesis. METHODS: 180 adolescents (mean age = 19.1 years; 68.9 % female) with diverse racial and ethnic identities (56.1 % White; 28.3 % Hispanic; 26.1 % Asian) participated. The Childhood Trauma Interview was administered to quantify early adversity. Five inflammatory biomarkers were assayed in antecubital blood - C-reactive protein, tumor necrosis factor-a, and interleukins-6, -8, and -10 - and were averaged to form a composite score. Participants also completed a functional MRI task to measure corticostriatal responsivity to the anticipation and acquisition of monetary rewards. RESULTS: Stress exposure and corticostriatal responsivity interacted statistically to predict the inflammation composite. Among participants who experienced major stressors in the first decade of life, higher inflammatory activity covaried with lower corticostriatal responsivity during acquisition of monetary rewards. This relationship was specific to participants who experienced major stress in early childhood, implying a sensitive period for exposure, and were evident in both the orbitofrontal cortex and the ventral striatum, suggesting the broad involvement of corticostriatal regions. The findings were independent of participants' age, sex, racial and ethnic identity, family income, and depressive symptoms. CONCLUSIONS: Collectively, the results are consistent with hypotheses suggesting that major stress in childhood alters brain-immune signaling.

Associations between thalamocortical functional connectivity and sensory over-responsivity in infants at high likelihood for ASD.

Despite growing evidence implicating thalamic functional connectivity atypicalities in autism spectrum disorder (ASD), it remains unclear how such alterations emerge early in human development. Because the thalamus plays a critical role in sensory processing and neocortical organization early in life, its connectivity with other cortical regions could be key for studying the early onset of core ASD symptoms. Here, we investigated emerging thalamocortical functional connectivity in infants at high (HL) and typical (TL) familial likelihood for ASD in early and late infancy. We report significant thalamo-limbic hyperconnectivity in 1.5-month-old HL infants, and thalamo-cortical hypoconnectivity in prefrontal and motor regions in 9-month-old HL infants. Importantly, early sensory over-responsivity (SOR) symptoms in HL infants predicted a direct trade-off in thalamic connectivity whereby stronger thalamic connectivity with primary sensory regions and basal ganglia was inversely related to connectivity with higher order cortices. This trade-off suggests that ASD may be characterized by early differences in thalamic gating. The patterns reported here could directly underlie atypical sensory processing and attention to social vs. nonsocial stimuli observed in ASD. These findings lend support to a theoretical framework of ASD whereby early disruptions in sensorimotor processing and attentional biases early in life may cascade into core ASD symptomatology.

Age-related differences in resting-state functional connectivity from childhood to adolescence.

The human brain is active at rest, and spontaneous fluctuations in functional MRI BOLD signals reveal an intrinsic functional architecture. During childhood and adolescence, functional networks undergo varying patterns of maturation, and measures of functional connectivity within and between networks differ as a function of age. However, many aspects of these developmental patterns (e.g. trajectory shape and directionality) remain unresolved. In the present study, we characterised age-related differences in within- and between-network resting-state functional connectivity (rsFC) and integration (i.e. participation coefficient, PC) in a large cross-sectional sample of children and adolescents (n = 628) aged 8-21 years from the Lifespan Human Connectome Project in Development. We found evidence for both linear and non-linear differences in cortical, subcortical, and cerebellar rsFC, as well as integration, that varied by age. Additionally, we found that sex moderated the relationship between age and putamen integration where males displayed significant age-related increases in putamen PC compared with females. Taken together, these results provide evidence for complex, non-linear differences in some brain systems during development.

Cardiovascular and metabolic health is associated with functional brain connectivity in middle-aged and older adults: Results from the Human Connectome Project-Aging study.

Several cardiovascular and metabolic indicators, such as cholesterol and blood pressure have been associated with altered neural and cognitive health as well as increased risk of dementia and Alzheimer's disease in later life. In this cross-sectional study, we examined how an aggregate index of cardiovascular and metabolic risk factor measures was associated with correlation-based estimates of resting-state functional connectivity (FC) across a broad adult age-span (36-90+ years) from 930 volunteers in the Human Connectome Project Aging (HCP-A). Increased (i.e., worse) aggregate cardiometabolic scores were associated with reduced FC globally, with especially strong effects in insular, medial frontal, medial parietal, and superior temporal regions. Additionally, at the network-level, FC between core brain networks, such as default-mode and cingulo-opercular, as well as dorsal attention networks, showed strong effects of cardiometabolic risk. These findings highlight the lifespan impact of cardiovascular and metabolic health on whole-brain functional integrity and how these conditions may disrupt higher-order network integrity.

Impact of autism genetic risk on brain connectivity: a mechanism for the female protective effect.

The biological mechanisms underlying the greater prevalence of autism spectrum disorder in males than females remain poorly understood. One hypothesis posits that this female protective effect arises from genetic load for autism spectrum disorder differentially impacting male and female brains. To test this hypothesis, we investigated the impact of cumulative genetic risk for autism spectrum disorder on functional brain connectivity in a balanced sample of boys and girls with autism spectrum disorder and typically developing boys and girls (127 youth, ages 8-17). Brain connectivity analyses focused on the salience network, a core intrinsic functional connectivity network which has previously been implicated in autism spectrum disorder. The effects of polygenic risk on salience network functional connectivity were significantly modulated by participant sex, with genetic load for autism spectrum disorder influencing functional connectivity in boys with and without autism spectrum disorder but not girls. These findings support the hypothesis that autism spectrum disorder risk genes interact with sex differential processes, thereby contributing to the male bias in autism prevalence and proposing an underlying neurobiological mechanism for the female protective effect.

Results and insights from a phase I clinical trial of Lomecel-B for Alzheimer's disease.

HYPOTHESIS: We hypothesized that Lomecel-B, an allogeneic medicinal signaling cell (MSC) therapeutic candidate for Alzheimer's disease (AD), is safe and potentially disease-modifying via pleiotropic mechanisms of action. KEY PREDICTIONS: We prospectively tested the predictions that Lomecel-B administration to mild AD patients is safe (primary endpoint) and would provide multiple exploratory indications of potential efficacy in clinical and biomarker domains (prespecified secondary/exploratory endpoints). STRATEGY AND KEY RESULTS: Mild AD patient received a single infusion of low- or high-dose Lomecel-B, or placebo, in a double-blind, randomized, phase I trial. The primary safety endpoint was met. Fluid-based and imaging biomarkers indicated significant improvement in the Lomecel-B arms versus placebo. The low-dose Lomecel-B arm showed significant improvements versus placebo on neurocognitive and other assessments. INTERPRETATION: Our results support the safety of Lomecel-B for AD, suggest clinical potential, and provide mechanistic insights. This early-stage study provides important exploratory information for larger efficacy-powered clinical trials.

Individual differences in threat and reward neural circuitry activation: Testing dimensional models of early adversity, anxiety and depression.

Altered functioning of the brain's threat and reward circuitry has been linked to early life adversity and to symptoms of anxiety and depression. To date, however, these relationships have been studied largely in isolation and in categorical-based approaches. It is unclear to what extent early life adversity and psychopathology have unique effects on brain functioning during threat and reward processing. We examined functional brain activity during a face processing task in threat (amygdala and ventromedial prefrontal cortex) and reward (ventral striatum and orbitofrontal cortex) regions of interest among a sample (N = 103) of young adults (aged 18-19 years) in relation to dimensional measures of early life adversity and symptoms of anxiety and depression. Results demonstrated a significant association between higher scores on the deprivation adversity dimension and greater activation of reward neural circuitry during viewing of happy faces, with the largest effect sizes observed in the orbitofrontal cortex. We found no significant associations between the threat adversity dimension, or symptom dimensions of anxiety and depression, and neural activation in threat or reward circuitries. These results lend partial support to theories of adversity-related alterations in neural activation and highlight the importance of testing dimensional models of adversity and psychopathology in large sample sizes to further our understanding of the biological processes implicated.

Atypical cerebellar functional connectivity at 9 months of age predicts delayed socio-communicative profiles in infants at high and low risk for autism.

BACKGROUND: While the cerebellum is traditionally known for its role in sensorimotor control, emerging research shows that particular subregions, such as right Crus I (RCrusI), support language and social processing. Indeed, cerebellar atypicalities are commonly reported in autism spectrum disorder (ASD), a neurodevelopmental disorder characterized by socio-communicative impairments. However, the cerebellum's contribution to early socio-communicative development remains virtually unknown. METHODS: Here, we characterized functional connectivity within cerebro-cerebellar networks implicated in language/social functions in 9-month-old infants who exhibit distinct 3-year socio-communicative developmental profiles. We employed a data-driven clustering approach to stratify our sample of infants at high (n = 82) and low (n = 37) familial risk for ASD into three cohorts-Delayed, Late-Blooming, and Typical-who showed unique socio-communicative trajectories. We then compared the cohorts on indices of language and social development. Seed-based functional connectivity analyses with RCrusI were conducted on infants with fMRI data (n = 66). Cohorts were compared on connectivity estimates from a-priori regions, selected on the basis of reported coactivation with RCrusI during language/social tasks. RESULTS: The three trajectory-based cohorts broadly differed in social communication development, as evidenced by robust differences on numerous indices of language and social skills. Importantly, at 9 months, the cohorts showed striking differences in cerebro-cerebellar circuits implicated in language/social functions. For all regions examined, the Delayed cohort exhibited significantly weaker RCrusI connectivity compared to both the Late-Blooming and Typical cohorts, with no significant differences between the latter cohorts. CONCLUSIONS: We show that hypoconnectivity within distinct cerebro-cerebellar networks in infancy predicts altered socio-communicative development before delays overtly manifest, which may be relevant for early detection and intervention. As the cerebellum is implicated in prediction, our findings point to probabilistic learning as a potential intermediary mechanism that may be disrupted in infancy, cascading into alterations in social communication.

A neurogenetic analysis of female autism.

Females versus males are less frequently diagnosed with autism spectrum disorder (ASD), and while understanding sex differences is critical to delineating the systems biology of the condition, female ASD is understudied. We integrated functional MRI and genetic data in a sex-balanced sample of ASD and typically developing youth (8-17 years old) to characterize female-specific pathways of ASD risk. Our primary objectives were to: (i) characterize female ASD (n = 45) brain response to human motion, relative to matched typically developing female youth (n = 45); and (ii) evaluate whether genetic data could provide further insight into the potential relevance of these brain functional differences. For our first objective we found that ASD females showed markedly reduced response versus typically developing females, particularly in sensorimotor, striatal, and frontal regions. This difference between ASD and typically developing females does not resemble differences between ASD (n = 47) and typically developing males (n = 47), even though neural response did not significantly differ between female and male ASD. For our second objective, we found that ASD females (n = 61), versus males (n = 66), showed larger median size of rare copy number variants containing gene(s) expressed in early life (10 postconceptual weeks to 2 years) in regions implicated by the typically developing female > female functional MRI contrast. Post hoc analyses suggested this difference was primarily driven by copy number variants containing gene(s) expressed in striatum. This striatal finding was reproducible among n = 2075 probands (291 female) from an independent cohort. Together, our findings suggest that striatal impacts may contribute to pathways of risk in female ASD and advocate caution in drawing conclusions regarding female ASD based on male-predominant cohorts.

Altered Thalamocortical Connectivity in 6-Week-Old Infants at High Familial Risk for Autism Spectrum Disorder.

Converging evidence from neuroimaging studies has revealed altered connectivity in cortical-subcortical networks in youth and adults with autism spectrum disorder (ASD). Comparatively little is known about the development of cortical-subcortical connectivity in infancy, before the emergence of overt ASD symptomatology. Here, we examined early functional and structural connectivity of thalamocortical networks in infants at high familial risk for ASD (HR) and low-risk controls (LR). Resting-state functional connectivity and diffusion tensor imaging data were acquired in 52 6-week-old infants. Functional connectivity was examined between 6 cortical seeds-prefrontal, motor, somatosensory, temporal, parietal, and occipital regions-and bilateral thalamus. We found significant thalamic-prefrontal underconnectivity, as well as thalamic-occipital and thalamic-motor overconnectivity in HR infants, relative to LR infants. Subsequent structural connectivity analyses also revealed atypical white matter integrity in thalamic-occipital tracts in HR infants, compared with LR infants. Notably, aberrant connectivity indices at 6 weeks predicted atypical social development between 9 and 36 months of age, as assessed with eye-tracking and diagnostic measures. These findings indicate that thalamocortical connectivity is disrupted at both the functional and structural level in HR infants as early as 6 weeks of age, providing a possible early marker of risk for ASD.

Identifying individuals with Alzheimer's disease-like brains based on structural imaging in the Human Connectome Project Aging cohort.

Given the difficulty in factoring out typical age effects from subtle Alzheimer's disease (AD) effects on brain structure, identification of very early, as well as younger preclinical "at-risk" individuals has unique challenges. We examined whether age-correction procedures could be used to better identify individuals at very early potential risk from adults who did not have any existing cognitive diagnosis. First, we obtained cross-sectional age effects for each structural feature using data from a selected portion of the Human Connectome Project Aging (HCP-A) cohort. After age detrending, we weighted AD structural deterioration with patterns quantified from data of the Alzheimer's Disease Neuroimaging Initiative. Support vector machine was then used to classify individuals with brains that most resembled atrophy in AD across the entire HCP-A sample. Additionally, we iteratively adjusted the pipeline by removing individuals classified as AD-like from the HCP-A cohort to minimize atypical brain structural contributions to the age detrending. The classifier had a mean cross-validation accuracy of 94.0% for AD recognition. It also could identify mild cognitive impairment with more severe AD-specific biomarkers and worse cognition. In an independent HCP-A cohort, 8.8% were identified as AD-like, and they trended toward worse cognition. An "AD risk" score derived from the machine learning models also significantly correlated with cognition. This work provides a proof of concept for the potential to use structural brain imaging to identify asymptomatic individuals at young ages who show structural brain patterns similar to AD and are potentially at risk for a future clinical disorder.

Associations between physiological and neural measures of sensory reactivity in youth with autism.

BACKGROUND: Individuals with Autism Spectrum Disorder (ASD) commonly show sensory over-responsivity (SOR), an impairing condition related to over-reactive brain and behavioral responses to aversive stimuli. While individuals with ASD often show atypically high physiological arousal, it is unclear how this relates to sensory reactivity. We therefore investigated how physiological arousal relates to brain and behavioral indices of SOR, to inform understanding of the biological mechanisms underlying SOR and to determine whether physiological measures are associated with SOR-related brain responses. METHODS: Youth aged 8-18 (49 ASD; 30 age- and performance-IQ-matched typically developing (TD)) experienced mildly aversive tactile and auditory stimuli first during functional magnetic resonance imaging (N = 41 ASD, 26 TD) and then during skin conductance (SCR) (N = 48 ASD, 28 TD) and heart rate (HR) measurements (N = 48 ASD, 30 TD). Parents reported on their children's SOR severity. RESULTS: Autism Spectrum Disorder youth overall displayed greater SCR to aversive sensory stimulation than TD youth and greater baseline HR. Within ASD, higher SOR was associated with higher mean HR across all stimuli after controlling for baseline HR. Furthermore, the ASD group overall, and the ASD-high-SOR group in particular, showed reduced HR deceleration/greater acceleration to sensory stimulation compared to the TD group. Both SCR and HR were associated with brain responses to sensory stimulation in regions previously associated with SOR and sensory regulation. CONCLUSIONS: Autism Spectrum Disorder youth displayed heightened physiological arousal to mildly aversive sensory stimulation, with HR responses in particular showing associations with brain and behavioral measures of SOR. These results have implications for using psychophysiological measures to assess SOR, particularly in individuals with ASD who cannot undergo MRI.

Lack of neural evidence for implicit language learning in 9-month-old infants at high risk for autism.

Word segmentation is a fundamental aspect of language learning, since identification of word boundaries in continuous speech must occur before the acquisition of word meanings can take place. We previously used functional magnetic resonance imaging (fMRI) to show that youth with autism spectrum disorder (ASD) are less sensitive to statistical and speech cues that guide implicit word segmentation. However, little is known about the neural mechanisms underlying this process during infancy and how this may be associated with ASD risk. Here, we examined early neural signatures of language-related learning in 9-month-old infants at high (HR) and low familial risk (LR) for ASD. During natural sleep, infants underwent fMRI while passively listening to three speech streams containing strong statistical and prosodic cues, strong statistical cues only, or minimal statistical cues to word boundaries. Compared to HR infants, LR infants showed greater activity in the left amygdala for the speech stream containing statistical and prosodic cues. While listening to this same speech stream, LR infants also showed more learning-related signal increases in left temporal regions as well as increasing functional connectivity between bilateral primary auditory cortex and right anterior insula. Importantly, learning-related signal increases at 9 months positively correlated with expressive language outcome at 36 months in both groups. In the HR group, greater signal increases were additionally associated with less severe ASD symptomatology at 36 months. These findings suggest that early differences in the neural networks underlying language learning may predict subsequent language development and altered trajectories associated with ASD risk.

Sex Differences in Functional Connectivity of the Salience, Default Mode, and Central Executive Networks in Youth with ASD.

Autism spectrum disorder (ASD) is associated with the altered functional connectivity of 3 neurocognitive networks that are hypothesized to be central to the symptomatology of ASD: the salience network (SN), default mode network (DMN), and central executive network (CEN). Due to the considerably higher prevalence of ASD in males, however, previous studies examining these networks in ASD have used primarily male samples. It is thus unknown how these networks may be differentially impacted among females with ASD compared to males with ASD, and how such differences may compare to those observed in neurotypical individuals. Here, we investigated the functional connectivity of the SN, DMN, and CEN in a large, well-matched sample of girls and boys with and without ASD (169 youth, ages 8-17). Girls with ASD displayed greater functional connectivity between the DMN and CEN than boys with ASD, whereas typically developing girls and boys differed in SN functional connectivity only. Together, these results demonstrate that youth with ASD exhibit altered sex differences in these networks relative to what is observed in typical development, and highlight the importance of considering sex-related biological factors and participant sex when characterizing the neural mechanisms underlying ASD.

Intellectual and developmental disabilities research centers: Fifty years of scientific accomplishments.

Progress in addressing the origins of intellectual and developmental disabilities accelerated with the establishment 50 years ago of the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health and associated Intellectual and Developmental Disabilities Research Centers. Investigators at these Centers have made seminal contributions to understanding human brain and behavioral development and defining mechanisms and treatments of disorders of the developing brain. ANN NEUROL 2019;86:332-343.

Defining and distinguishing infant behavioral states using acoustic cry analysis: is colic painful?

BACKGROUND: To characterize acoustic features of an infant's cry and use machine learning to provide an objective measurement of behavioral state in a cry-translator. To apply the cry-translation algorithm to colic hypothesizing that these cries sound painful. METHODS: Assessment of 1000 cries in a mobile app (ChatterBabyTM). Training a cry-translation algorithm by evaluating >6000 acoustic features to predict whether infant cry was due to a pain (vaccinations, ear-piercings), fussy, or hunger states. Using the algorithm to predict the behavioral state of infants with reported colic. RESULTS: The cry-translation algorithm was 90.7% accurate for identifying pain cries, and achieved 71.5% accuracy in discriminating cries from fussiness, hunger, or pain. The ChatterBaby cry-translation algorithm overwhelmingly predicted that colic cries were most likely from pain, compared to fussy and hungry states. Colic cries had average pain ratings of 73%, significantly greater than the pain measurements found in fussiness and hunger (p < 0.001, 2-sample t test). Colic cries outranked pain cries by measures of acoustic intensity, including energy, length of voiced periods, and fundamental frequency/pitch, while fussy and hungry cries showed reduced intensity measures compared to pain and colic. CONCLUSIONS: Acoustic features of cries are consistent across a diverse infant population and can be utilized as objective markers of pain, hunger, and fussiness. The ChatterBaby algorithm detected significant acoustic similarities between colic and painful cries, suggesting that they may share a neuronal pathway.

The Lifespan Human Connectome Project in Aging: An overview.

The original Human Connectome Project yielded a rich data set on structural and functional connectivity in a large sample of healthy young adults using improved methods of data acquisition, analysis, and sharing. More recent efforts are extending this approach to include infants, children, older adults, and brain disorders. This paper introduces and describes the Human Connectome Project in Aging (HCP-A), which is currently recruiting 1200 + healthy adults aged 36 to 100+, with a subset of 600 + participants returning for longitudinal assessment. Four acquisition sites using matched Siemens Prisma 3T MRI scanners with centralized quality control and data analysis are enrolling participants. Data are acquired across multimodal imaging and behavioral domains with a focus on factors known to be altered in advanced aging. MRI acquisitions include structural (whole brain and high resolution hippocampal) plus multiband resting state functional (rfMRI), task fMRI (tfMRI), diffusion MRI (dMRI), and arterial spin labeling (ASL). Behavioral characterization includes cognitive (such as processing speed and episodic memory), psychiatric, metabolic, and socioeconomic measures as well as assessment of systemic health (with a focus on menopause via hormonal assays). This dataset will provide a unique resource for examining how brain organization and connectivity changes across typical aging, and how these differences relate to key characteristics of aging including alterations in hormonal status and declining memory and general cognition. A primary goal of the HCP-A is to make these data freely available to the scientific community, supported by the Connectome Coordination Facility (CCF) platform for data quality assurance, preprocessing and basic analysis, and shared via the NIMH Data Archive (NDA). Here we provide the rationale for our study design and sufficient details of the resource for scientists to plan future analyses of these data. A companion paper describes the related Human Connectome Project in Development (HCP-D, Somerville et al., 2018), and the image acquisition protocol common to both studies (Harms et al., 2018).

The joint effect of aging and HIV infection on microstructure of white matter bundles.

Recent evidence suggests the aging process is accelerated by HIV. Degradation of white matter (WM) has been independently associated with HIV and healthy aging. Thus, WM may be vulnerable to joint effects of HIV and aging. Diffusion-weighted imaging (DWI) was conducted with HIV-seropositive (n = 72) and HIV-seronegative (n = 34) adults. DWI data underwent tractography, which was parcellated into 18 WM tracts of interest (TOIs). Functional Analysis of Diffusion Tensor Tract Statistics (FADTTS) regression was conducted assessing the joint effect of advanced age and HIV on fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) along TOI fibers. In addition to main effects of age and HIV on WM microstructure, the interactive effect of age and HIV was significantly related to lower FA and higher MD, AD, and RD across all TOIs. The location of findings was consistent with the clinical presentation of HIV-associated neurocognitive disorders. While older age is related to poorer WM microstructure, its detrimental effect on WM is stronger among HIV+ relative to HIV- individuals. Loss of WM integrity in the context of advancing age may place HIV+ individuals at increased risk for brain and cognitive compromise.

Altered lateralization of dorsal language tracts in 6-week-old infants at risk for autism.

Altered structural connectivity has been identified as a possible biomarker of autism spectrum disorder (ASD) risk in the developing brain. Core features of ASD include impaired social communication and early language delay. Thus, examining white matter tracts associated with language may lend further insight into early signs of ASD risk and the mechanisms that underlie language impairments associated with the disorder. Evidence of altered structural connectivity has previously been detected in 6-month-old infants at high familial risk for developing ASD. However, as language processing begins in utero, differences in structural connectivity between language regions may be present in the early infant brain shortly after birth. Here we investigated key white matter pathways of the dorsal language network in 6-week-old infants at high (HR) and low (LR) risk for ASD to identify atypicalities in structural connectivity that may predict altered developmental trajectories prior to overt language delays and the onset of ASD symptomatology. Compared to HR infants, LR infants showed higher fractional anisotropy (FA) in the left superior longitudinal fasciculus (SLF); in contrast, in the right SLF, HR infants showed higher FA than LR infants. Additionally, HR infants showed more rightward lateralization of the SLF. Across both groups, measures of FA and lateralization of these pathways at 6 weeks of age were related to later language development at 18 months of age as well as ASD symptomatology at 36 months of age. These findings indicate that early differences in the structure of language pathways may provide an early predictor of future language development and ASD risk.