Supplementary Materials and Methods

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Supplementary Materials and Methods

Patient cohorts and HAND diagnosis. The diagnosis of HAND versus nonHAND involved a multi-step clinical assessment, including assessment of neuropsychiatric symptoms (impairment in memory, concentration, motor functions and gait) conveyed through self-report or by the patient’s caregiver/family member and verified by neuropsychological testing, neurological and medical assessments and neuroimaging. Two cohorts were analysed: the Discovery Cohort was a retrospective cohort consisting of SAC patients from 1998 with stored samples; the Validation Cohort is a prospective cohort. In the Discovery Cohort , if neurocognitive impairment was suspected based on reported symptoms by patients (or caregivers), a brief neuropsychological test battery was applied including Symbol-Digit Modalities test, Grooved Pegboard, Trails A and Trails B together with repeated clinical assessments, neuroimaging and review by the clinical team for diagnostic consensus. For the Validation Cohort , a more comprehensive

neuropsychological assessment was implemented including pre-morbid estimate of IQ: WRAT Word Reading followed by analyses of five cognitive domains: Attention (Symbol Digit Modalities Test SDMT, D-KEFS Trail Making Test 2); Language (D-KEFS letter fluency; D- KEFS category fluency); Memory (Hopkins Verbal Learning Test); Motor (Grooved Pegboard), Executive Functions (short version of the Wisconsin Card Sorting Test WCST; D-KEFS Trail Making Test 4) to patients randomly selected from the active SAC patient population. For both cohorts, all patients’ complete medical and social histories were reviewed, which involved screening for prior neurological disorders (e.g., traumatic head injury, psychiatric disorders, CNS opportunistic diseases, and substance abuse) together with a physical examination,

neuroimaging, and cerebrospinal fluid analyses to exclude other causes of neurocognitive impairment. The diagnosis or absence of HAND was determined based on the consensus

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assessments by the SAC clinical team. Based on these diagnostic tests and assessments, HAND subjects were classified as exhibiting ANI, MND or HAD. Routine laboratory tests were performed on all patients’ samples immediately after diagnosis. The socio-demographic parameters of each patient were also collected. Written consent (approved by the University of Calgary Human Ethics Committee, E-17256) was obtained from each subject and blood samples were collected from each subject at the time of neurological assessment from which plasma was harvested and stored at -80°C.

MicroRNA extraction from plasma samples

Blood (5ml) was collected in EDTA tubes, from all subjects from which plasma was collected at the time of clinical assessment and spun at 1500 RPM for 10 min within four hours of collection.

Aliquots were prepared and stored at -80°C. For optimal extraction of micro-RNA, we used the miRNeasy Serum/Plasma kit (Qiagen) for extraction of total RNA including microRNA from plasma samples of patients according to manufacturer’s protocol with slight modification.

Plasma samples were centrifuged to remove any proteins or lipids that could inhibit the

extraction process. 200µl of sample was diluted with an equal amount of RNase free water. One volume of diluted plasma was mixed with five volumes of Qiazol, centrifuged at 1200g for 15 minutes at 4 °C and supernatant collected into a new tube. After incubation at room temperature for 5 minutes, 200µl of chloroform was added, vortexed and incubated for 15 minutes. The remaining steps were performed according to the manufacturer’s protocol from step 6 onward (Qiagen). Samples were analysed for the quality of RNA using Bioanalyzer 2100.

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Quantitative real-time reverse transcription polymerase chain reaction

Total RNA was extracted using the miRNeasy serum/plasma kit, as described above. The miRCURY locked nucleic acid (LNA) universal RT microRNA PCR (Exiqon) protocol involving the first-strand cDNA synthesis and real time PCR amplification was used according to manufacturer’s instruction. For first-strand cDNA synthesis, 4 µl of total RNA was used for reverse transcription in a total reaction volume of 10µl. Exiqon miRCURY LNA PCR primer assay (product number: 206999 and 2100158 for miR-4516 and miR-3665 respectively) and diluted cDNA (1:20) was used for qRT-PCR amplification according to manufacturer’s instruction. The Exiqon LNA PCR primer assay miR-4707-5p (product number 2116591 and 206999) was also used for qRT-PCR. MicroRNA expression data was normalized using Exiqon LNA primer assay miR-16-5p (product number 205702).

Statistics and bioinformatics analyses.

Two independent software packages including; Affymetrix Expression and Transcription Console (ETC) and GeneSpring version 12.6 (Agilent Technologies) were used to normalize the data and determine differentially expressed miRNAs. The normalization in both software packages was based on the Robust Multi-array Average (RMA) algorithm, in which data are background-corrected, log2 transformed and quartile normalized. To identify differentially expressed miRNAs, the median of each probe-set in the HAND or nonHAND patients was calculated and the significance of any differences determined by Mann-Whitney unpaired test on data subjected to Affymetrix and GeneSpring normalization, respectively. A cut-off fold change (>2) in relative miRNA abundance was applied and a p-value of <0.05 was considered statistically significant. Bioinformatics tools (miRDB, http://mirdb.org/miRDB/; Diana-microT v3.0, http://diana.cslab.ece.ntua.gr/microT/; and TargetScan v6.2, http://www.targetscan.org/)

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were used to predict gene targets. Predicted targets genes confirmed by at least two bioinformatics tools were uploaded into DAVID version 6.7 (http://david.abcc.ncifcrf.gov/) and analysis was performed to identify functional classes. Independent samples t and chi-squared tests were used to compare patient variables in HAND and nonHAND groups for both Discovery and Validation Cohorts. Univariate logistic regression was used to identify variables that predicted HAND. Multivariate logistic regression was used to identify combinations of miRNAs that predicted HAND. Spearman correlations were used to test linear relationships between CD4 T cell nadir or current CD4 T cell levels as well as expression of individual miRNAs. Receiver- operating characteristic (ROC) curve analyses were used to estimate an optimal classifier for HAND or nonHAND status using each of the miRNAs obtained from array hybridization or qRT-PCR technique. Mann-Whitney U test was used to compare the relative fold change of miRNA expression obtained from qRT-PCR in HAND and nonHAND. All statistical analyses were performed using Graphpad Prism (version 6.0) or R statistical software (version 3.0.2).

Differentially expressed miRNAs together with the fold change in medians between the two groups was interpreted as a dataset by Ingenuity Pathway Analysis. Networks of interacting miRNAs and mRNAs were generated using the core analysis function considering all available databases and including experimentally verified miRNA targets and those predicted with high probability.

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Supplementary Fig. 1: Study design. A screening cohort (Discovery Cohort) of HIV/AIDS patients was examined based on retrospective analyses (HAND, n=22; nonHAND, n=25). A prospective validation cohort (Validation Cohort) of HIV/AIDS patients was established (HAND, n=12; nonHAND, n=12). Identification of miRNAs associated with HAND in both cohorts was performed by array hybridization. Common miRNAs were identified and

individually validated by qRT-PCR. Bioinformatic and statistical software packages were used to determine putative genes targeted by individual miRNAs and miRNA diagnostic predictions of HAND.

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Supplementary Fig. 2: Prediction of HAND by miRNA expression. (A) Univariate logistic regression-derived predictive values of HAND for each miRNA and other independent variables.

(B) Multivariate logistic regression-derived predictive values of HAND for single or a

combination of miRNAs. (spectral values: A) 0 (blue) to 1.0 (orange); B) +1.0 (orange) to -1.0 (blue)).

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Supplementary Fig. 3: Network analyses of miRNAs identified in the Validation Cohort and the three common miRNAs. (A) Network analyses of miRNAs that showed differential

expression (threshold value >2.0) in the Validation Cohort when analyzed by Affymetrix ETC (IPA score: 28). Analysis considered miRNA-mRNA interactions that have been experimentally verified or predicted with a high probability from all available databases. Genes found to be increased (red) or decreased (green) in HAND are highlighted.The solid lines indicate direct interactions while dashed lines indicate indirect interactions. (B) Network analyses of miRNAs miR-3665, miR-3665, and miR-4707-5p predicted targets involved in myelination, cell-cycle, apoptosis and mitochondrial function.

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Supplementary Table 1: Differentially expressed miRNAs by affymetrix in Discovery Cohort

miRNA Fold Change P-Value

hsa_miR_3665 2.017625 0.041429564

hsa_miR_4651 2.043944 0.004374978

hsa_miR_4707_5p 2.359826 0.026414389

hsa_miR_4466 2.463749 0.022733605

hsa_miR_2861 2.526932 0.029886229

hsa_miR_1228_star 2.543841 0.003412433

hsa_miR_3656 2.882338 0.003586817

hsa_miR_4687_3p 2.984944 0.000490195 hsa_miR_3940_5p 3.498495 0.001226895

hsa_miR_3196 5.854257 0.011942413

hsa_miR_663 6.643431 0.034492227

hsa_miR_4516 6.670681 0.015971907

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Supplementary Table 2: Differentially expressed miRNAs by genespring in Discovery Cohort

miRNA Fold Change P-Values

hsa-miR-4687-3p 3 2.90E-04

hsa-miR-3196 2.8

0.007699

hsa-miR-3656 2.8

0.001106

hsa-miR-3940-5p 2.7

0.00214

hsa-miR-1228-star 2.6

0.012615

hsa-miR-663 2.6

0.036675

hsa-miR-4516 2.4

0.034799

hsa-miR-149-star 2.2

0.005578

hsa-miR-4466 2.1

0.003999

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Supplementary Table 3: Differentially expressed miRNAs by affymetrix in Discovery Cohort

hsa-miR-3613-5p 5.05 0.030202

hsa-miR-4532 4.25 0.00011

hsa-miR-1281 3.85 0.001627

hsa-miR-4487 3.34 0.000477

hsa-miR-3665 3.08 0.001795

hsa-miR-4507 3.04 0.002925

hsa-miR-4707-5p 2.72 0.005772

hsa-miR-1469 2.59 0.000369

hsa-miR-638 2.55 0.00036

hsa-miR-4787-5p 2.4 0.001359

hsa-miR-4763-3p 2.35 0.005766

hsa-miR-4488 2.28 0.037953

hsa-miR-3960 2.24 0.004072

hsa-miR-378h 2.09 0.015521

hsa-miR-106a -2.07 0.007053

hsa-miR-433 -2.14 0.004771

hsa-miR-486-3p -2.14 0.032722

hsa-miR-532-5p -2.18 0.01151

hsa-miR-431 -2.25 0.00043

hsa-miR-223 -2.35 0.005038

hsa-miR-199b-3p -2.4 0.007498

hsa-miR-199a-3p -2.43 0.009374

hsa-miR-93-star -2.55 0.00106

hsa-miR-15b -2.56 0.01067

hsa-miR-130a -2.65 0.049203

hsa-miR-330-3p -2.65 0.012617

hsa-miR-106b-star -3.15 0.004271

hsa-miR-339-3p -3.15 0.02004

hsa-miR-125a-5p -3.2 0.000992

hsa-miR-27a -3.76 0.003445

hsa-miR-127-3p -3.98 0.000067

hsa-miR-106b -4.23 0.043808

hsa-let-7i -4.77 0.000347

hsa-miR-20a -4.92 0.001067

hsa-miR-151-5p -4.96 0.032893

hsa-miR-26a -5.1 0.02323

hsa-miR-25 -5.19 0.00371

hsa-miR-451 -5.33 0.048469

hsa-miR-432 -5.51 0.000906

hsa-miR-342-3p -5.56 0.01244

hsa-miR-652 -5.81 0.020641

hsa-miR-20b -5.91 0.00015

hsa-miR-99b -6.36 0.016431

hsa-miR-222 -6.97 0.017683

hsa-miR-18a -8.5 0.000386

hsa-miR-134 -10.43 0.009922

hsa-miR-409-3p -15.2 0.000273

hsa-miR-382 -15.62 0.001467

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Supplementary Table 4: Differentially expressed miRNAs by genespring in cohort 2

hsa-let-7d -2.001406 0.043308

hsa-miR-17 -3.4531918 0.001496

hsa-miR-18a -4.6710124 0.004669

hsa-miR-20a -5.23228 0.001496

hsa-miR-23a -4.0790133 0.011074

hsa-miR-24 -2.6109416 0.037667

hsa-miR-25 -4.0177193 0.006657

hsa-miR-26a -3.6875432 0.032663

hsa-miR-27a -3.8757453 0.005584

hsa-miR-93 -3.353435 0.013043

hsa-miR-93-star -2.1144204 0.001224

hsa-miR-103a -2.5140243 0.013043

hsa-miR-106a -4.13424 0.00268

hsa-miR-107 -2.4444716 0.02824

hsa-miR-199a-5p -2.344816 0.003892

hsa-miR-199a-3p -2.5944173 0.009375 hsa-miR-199b-3p -2.6254444 0.049598

hsa-miR-222 -3.1663306 0.020921

hsa-miR-223 -2.671069 0.037667

hsa-let-7i -4.0360837 0.005584

hsa-miR-15b -2.4146245 0.024343

hsa-miR-125a-5p -2.6632214 0.005098

hsa-miR-126 -2.469669 0.02824

hsa-miR-127-3p -3.4752998 6.58E-04

hsa-miR-134 -4.118303 0.02422

hsa-miR-106b -2.6769738 0.011074

hsa-miR-106b-star -2.4487362 0.032663

hsa-miR-99b -2.6016386 0.024343

hsa-miR-382 -6.026357 0.013043

hsa-miR-342-3p -2.8361144 0.013043

hsa-miR-151-5p -3.2423902 0.020921

hsa-miR-339-3p -2.2924082 0.017926

hsa-miR-20b -4.0999055 5.32E-04

hsa-miR-431 -2.332036 8.12E-04

hsa-miR-433 -2.0423496 0.003222

hsa-miR-451 -3.1529553 0.049647

hsa-miR-652 -3.5032096 0.011057

hsa-miR-638 3.340306 0.002214

hsa-miR-3185 2.2629225 0.043308

hsa-miR-3613-5p 3.4819577 0.02824

hsa-miR-3665 2.926382 0.003892

hsa-miR-4487 3.345515 0.00268

hsa-miR-4507 2.9349456 0.004669

hsa-miR-4516 2.3020766 0.020921

hsa-miR-4532 3.9586976 8.12E-04

hsa-miR-3960 2.5087786 0.020921

hsa-miR-4707-5p 2.6226518 0.011074

hsa-miR-4763-3p 2.333299 0.013043

hsa-miR-4787-5p 2.7680485 0.004669

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Supplementary Table 5: miR-3665 predicted gene targets.

Gene Symbol Gene Name Function

PXT1 peroxisomal, testis specific 1 Apoptosis

LRP1B low density lipoprotein receptor-related protein 1B Inflammation, endocytosis and signal transduction

IL21R interleukin 21 receptor Immunity & Inflammation

SEMA6D sema domain, transmembrane domain (TM), and cytoplasmic domain, (semaphorin) 6D

CNS development

IRAK2 interleukin-1 receptor-associated kinase 2 Transcription, immunity and inflammation

SLC4A5 solute carrier family 4, sodium bicarbonate cotransporter, member 5

transport

SEPT11 septin 11 Cell growth

YAF2 YY1 associated factor 2 transcription

ETV6 ets variant 6 transcription

ABCG4 ATP-binding cassette, sub-family G (WHITE), member 4 metabolism

TRIM46 tripartite motif containing 46 unknown

NLGN3 neuroligin 3 CNS development

TRAF1 TNF receptor-associated factor 1 Signaling, anti-apoptosis IL1A interleukin 1, alpha Immunity & Inflammation

EVL Enah/Vasp-like Axon guidance

VDR vitamin D (1,25- dihydroxyvitamin D3) receptor transcription

Bold face genes indicate published interaction with HIV-1.

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Supplementary Table 6: miR-4516 predicted gene targets.

NTRK2 neurotrophic tyrosine kinase, receptor, type 2 CNS development

LRP4 low density lipoprotein receptor-related protein 4 Neuromuscular junction and Wnt signalling

ETV4 ets variant 4 transcription

GRAMD2 GRAM domain containing 2 unknown

CDK2AP2 cyclin-dependent kinase 2 associated protein 2 Stem cell Differentiation CMTM4 CKLF-like MARVEL transmembrane domain containing 4 Cell growth and Cell cycle

GIGYF1 GRB10 interacting GYF protein 1 signaling

AHCYL2 adenosylhomocysteinase-like 2 metabolism

TRIM46 tripartite motif containing 46 unknown

CD93 CD93 molecule Phagocytosis & adhesion

ING4 inhibitor of growth family, member 4 DNA replication ING3 inhibitor of growth family, member 3 transcription

NLGN2 neuroligin 2 CNS development

SPRY4 sprouty homolog 4 (Drosophila) MAPK signaling

CCR5 chemokine (C-C motif) receptor 5 Immunity & Inflammation DDX6 DEAD (Asp-Glu-Ala-Asp) box polypeptide 6 mRNA degradation DDX17 DEAD (Asp-Glu-Ala-Asp) box polypeptide 17 ATPase activity

CXCL9 chemokine (C-X-C motif) ligand 9 Immunity & Inflammation CCL22 chemokine (C-C motif) ligand 22 Immunity & Inflammation PCSK1 proprotein convertase subtilisin/kexin type 1 Cleavage of proteins

MSN Moesin Cell-cell recognition and signalling

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Supplementary Table 7: miR-4707-5p predicted gene targets

TGIF1 TGFB-induced factor homeobox 1 Transcription

SEMA6B sema domain, transmembrane domain (TM), and cytoplasmic domain, (semaphorin) 6B

CNS development

ATP2C2 ATPase, Ca++ transporting, type 2C, member 2 Hydrolysis of ATP NMNAT3 nicotinamide nucleotide adenylyltransferase 3 metabolism BCAS4 breast carcinoma amplified sequence 4 unknown

FSTL3 follistatin-like 3 (secreted glycoprotein) Role in leukemogenesis ERG v-ets erythroblastosis virus E26 oncogene homolog (avian) Transcription

STK35 serine/threonine kinase 35 metabolism

ACTN2 actinin, alpha 2 Binding active to membranes

CBX6 chromobox homolog 6 Transcription

ATP6V0D2 ATPase, H+ transporting, lysosomal 38kDa, V0 subunit d2 Hydrolysis of ATP

IAPP islet amyloid polypeptide metabolism

NRSN2 neurensin 2 transport

CCDC47 coiled-coil domain containing 47 Signaling and immunity APOBEC3D apolipoprotein B mRNA editing enzyme, catalytic

polypeptide-like 3D

Antiviral activity

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